DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Pending
1-15
35 U.S.C. 103
1-15
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d), regarding Application No. CN 202311863182.0, filed on filed 12/29/2023.
Information Disclosure Statement
The information disclosure statement(s) (IDS(s)) submitted on 10/19/2025 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitation(s) is/are: image acquisition device in claims 1, 2, 8, 9; pallet diversion device in claims 1, 8; channel attention mechanism and spatial attention mechanism in claims 5, 12; first diversion device in claims 6, 13; second diversion device in claims 6, 13; and third diversion device in claims 7, 14.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
The specification discloses the corresponding structure for: image acquisition device, pallet diversion device, first diversion device, second diversion device, and third diversion device in paragraph [0030], and channel attention mechanism and spatial attention mechanism in paragraphs [0072] and [0077].
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-4, 6-11, 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (CN 111086693 A, “Wu”, provided by applicant in IDS filed 10/19/2025) and further in view of Inada et al. (US 5,359,408 A, “Inada”).
Regarding Claim 1: Wu teaches: A pallet recycling method, applied to an electronic device comprised in a yarn spindle packaging system, wherein the electronic device communicates with an image acquisition device and a pallet diversion device respectively; and wherein the method comprises: ([0002] automatic roll stacking and packaging. [0023] system, conveying device, processor, control device, readable storage medium, controlling the roll-online robot, the palletizing device, the packaging device and the conveying device to automatically palletize and package the roll. Fig. 3: pallets 72, yarn spindles 71, shows packaging system for yarn spindles on pallets)
after a robot grabs M yarn spindles to be packaged from a yarn spindle trolley through N grippers, controlling the [appearance detection module to detect the appearance of the yarn spindles]; wherein each of the N grippers is capable of grabbing one yarn spindle to be packaged, N≥2 and N is an integer, 0≤M≤N and M is an integer; and ([0016] grabs multiple rolls by multiple grippers arranged on the robot and obtains grade info of each package corresponding to the grippers one by one. [0069] robot grippers have two adjacent appearance detection modules. [0015] weight detection of roll, appearance detection of roll, and grade info based on these detections. [0060] optical weight (mass) estimation sensor)
after the robot places the M yarn spindles to be packaged one by one on M yarn spindle pallets comprised in a target pallet group arranged on a main line of an assembly line (Fig. 3: robot 1, yarn spindle pallets 72, assembly line 2, yarn spindles 71),
and when determining that there is [a pallet] in the target pallet group [based on the appearance detection], controlling the pallet diversion device to divert [the pallet] from the main line of the assembly line to a branch line of the assembly line […]; wherein [the pallet is …] or a second pallet to be recycled on which a yarn spindle to be packaged is initially evaluated as a graded yarn spindle ([0015] weight detection of roll, appearance detection of roll, and grade info based on these detections. [0021] roll with first grade is placed at first palletizing station and palletized as roll with first grade; roll with second grade placed a second palletizing station and palletized as roll with second grade. [0062] packages processed separately according to their grade info (winding and storage processes might cause loose threads, intactness issues). [0004] during boxing and palletizing the packages, the packages need to be inspected for weight and appearance. [0005] fully automatic intelligent packaging system for chemical fiber DTY spindles, which includes a spindle entry track and a serpentine track. An intelligent inspection and classification system. inspect the weight and dyeing grade of spindles of different batches and models, classify, and grade spindles of different batches and models).
However, Wu does not explicitly teach: controlling the image acquisition device to shoot towards the N grippers to obtain a grabbing result representation image; determining that there is a pallet to be recycled … based on the grabbing result representation image, divert the pallet to be recycled [from main line to a branch line of the assembly line to] realize recycling of the pallet to be recycled; wherein the pallet to be recycled is an empty first pallet to be recycled.
Inada teaches: controlling the image acquisition device to shoot towards the N grippers to obtain a grabbing result representation image; (Col. 5, “camera, mounted nearly at right angles with the axis of the bobbin B, producing an image,” “focus of the area sensor 107 is positioned at a mean value of the radii of the package P and large-diameter flange 103.” Col. 6, “camera mounted in the inspection box for checking a package,” “photographed by a camera.” Col. 8, “cameras 224 and 225 start photographing. Concretely, image signals from the cameras 224 and 225 are processed by a computer, which judges the presence or absence of a bunch winding and a bulge winding”)
determining that there is a pallet to be recycled … based on the grabbing result representation image, (Col. 6, “This inspection apparatus 201 is equipped with a conveyor 203 for carrying the package P on the tray 202. This conveyor 203 is arranged on the upper stage of the frame 204. On the lower stage of the frame 204 is installed a return conveyor 205 for returning the tray202.” Cols. 8-9, “The tray 202 thus removed of the package P is then transferred by a transfer apparatus 240 over to the return conveyor 205 and furthermore transferred, for a reuse purpose, by the transfer apparatus 241 from the return conveyor 205 over to the conveyor 203.”)
divert the pallet to be recycled [from main line to a branch line of the assembly line to] realize recycling of the pallet to be recycled; wherein the pallet to be recycled is an empty first pallet to be recycled (Col. 8, “At the discharge end of the conveyor 203 is mounted a transfer apparatus 240 for transferring an empty tray 202 onto the return conveyor 205. Furthermore at the entrance end of the conveyor 203 is mounted a transfer apparatus 241 for transferring the empty tray 202 from the return conveyor 205 over to the conveyor 203”).
Wu and Inada are analogous art to the claimed invention since they are from the similar field of pallet recycling and yarn spindle packaging. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Wu with the aspects of Inada to create, with a reasonable expectation for success, a pallet recycling method that controls the image acquisition device to shoot towards the grippers to obtain an image, determines a pallet to be recycled, diverts the pallet to be recycled, wherein the pallet to be recycled is an empty first pallet to be recycled. The motivation for modification would have been to increase the efficiency of inspection and palletization of yarn spindles, by automating inspection using cameras and sensors (Inada, Col. 4). The motivation for modification is similarly applied to those claims which depend upon claim 1.
Regarding Claim 2: Wu-Inada further teach: The method of claim 1, wherein the electronic device further communicates with the robot; (Wu: [0071] gripper includes detection control module which maintains communication connection with weight and appearance detection modules)
wherein the controlling the image acquisition device to shoot towards the N grippers to obtain a grabbing result representation image, comprises: (Wu: [0069], [0015], [0004]. Inada: Col. 5, Col. 8, image signals from the cameras)
controlling the N grippers to rotate relative to the image acquisition device; controlling the image acquisition device to shoot towards the N grippers to obtain Z images to be processed during rotation of the N grippers relative to the image acquisition device; wherein Z≥2 and Z is an integer, and the Z images to be processed correspond to different viewing angles of the N grippers; and obtaining the grabbing result representation image based on the Z images to be processed (Wu: [0016] grabs multiple rolls by multiple grippers arranged on the robot and obtains grade info of each package one by one. [0069] grippers have two adjacent appearance detection modules. [0015] weight detection of roll, appearance detection of roll, and grade info based on these detections. [0060] optical weight (mass) estimation sensor. Fig. 3: robot 1, yarn spindle pallets 72, assembly line 2, yarn spindles 71. Inada: Col. 5, “camera, mounted nearly at right angles with the axis of the bobbin B, producing an image,” “focus of the area sensor 107 is positioned at a mean value of the radii of the package P and large-diameter flange 103.” Col. 6, “camera mounted in the inspection box for checking a package,” “photographed by a camera.” Col. 8, “cameras 224 and 225 start photographing. Concretely, image signals from the cameras 224 and 225 are processed by a computer, which judges the presence or absence of a bunch winding and a bulge winding”).
Regarding Claim 3: Wu-Inada further teach: The method of claim 2, wherein the obtaining the grabbing result representation image based on the Z images to be processed, comprises: intercepting N single-view images from each of the Z images to be processed to obtain N×Z single-view images; wherein the N single-view images correspond to the N grippers one by one; splicing Z single-view images corresponding to a same gripper among the N×Z single-view images to obtain N multi-view images; and obtaining the grabbing result representation image based on the N multi-view images (Wu: [0016] grabs multiple rolls by multiple grippers arranged on the robot and obtains grade info of each package corresponding to the grippers one by one. [0069] robot grippers have two adjacent appearance detection modules. [0015] weight detection of roll, appearance detection of roll, and grade info based on these detections. [0060] optical weight (mass) estimation sensor. Fig. 3: robot 1, yarn spindle pallets 72, assembly line 2, yarn spindles 71. Inada: Col. 5, “camera, mounted nearly at right angles with the axis of the bobbin B, producing an image,” “focus of the area sensor 107 is positioned at a mean value of the radii of the package P and large-diameter flange 103.” Col. 6, “camera mounted in the inspection box for checking a package,” “photographed by a camera.” Col. 8, “cameras 224 and 225 start photographing. Concretely, image signals from the cameras 224 and 225 are processed by a computer, which judges the presence or absence of a bunch winding and a bulge winding”).
Regarding Claim 4: Wu-Inada further teach: The method of claim 1, wherein the grabbing result representation image comprises N multi-view images corresponding to the N grippers one by one, and the target pallet group comprises a total of N yarn spindle pallets corresponding to the N grippers one by one, to establish a one-to-one correspondence between the N yarn spindle pallets and the N multi-view images; (Wu: [0016]. [0069]. [0015]. [0060]. Fig. 3: robot 1, yarn spindle pallets 72, assembly line 2, yarn spindles 71. Inada: Col. 5, camera, mounted nearly at right angles with the axis of the bobbin, focus of area sensor is positioned at a mean value of the radii, Col. 6, camera mounted in inspection box for checking package, photographed by camera, Col. 8, cameras start photographing. Images processed by computer, judges presence or absence of bunch and bulge winding)
wherein the determining that there is a pallet to be recycled in the target pallet group based on the grabbing result representation image, comprises: (Wu: [0015], [0021], [0062], [0004]-[0005]. Inada: Col. 6, return conveyor returns tray. Cols. 8-9, transfer tray from return conveyor to conveyor to reuse)
for each of the N multi-view images, when determining that there is no yarn spindle image for representing a yarn spindle to be packaged in the multi-view image, determining that there is a pallet to be recycled in the target pallet group, and taking a yarn spindle pallet corresponding to the multi-view image among the N yarn spindle pallets as the first pallet to be recycled; and (Wu: [0004] inspected. [0005] inspect the weight and dyeing grade of spindles of different batches and models, classify, and grade spindles of different batches and models. [0015] weight, appearance, grade. [0016] obtains grade info of each package one by one. [0021]. [0062] packages processed separately according to their grade info. Inada: Col. 8, cameras start photographing. Images processed by a computer, judges bunch or bulge winding. end of conveyor has transfer apparatus for transferring an empty tray onto the return conveyor. at the entrance end of the conveyor is mounted a transfer apparatus for transferring the empty tray from the return conveyor over to the conveyor. Cols. 8-9, tray emptied, then transferred over to the return conveyor and transferred, for a reuse purpose, from the return conveyor over to the conveyor)
when determining that there is a yarn spindle image for representing a yarn spindle to be packaged in the multi-view image and determining that the yarn spindle image has a defect feature through a defect detection network, determining that there is a pallet to be recycled in the target pallet group, and taking a yarn spindle pallet corresponding to the multi-view image among the N yarn spindle pallets as the second pallet to be recycled (Wu: [0005] inspect the weight and dyeing grade of spindles of different batches and models, classify, and grade spindles of different batches and models. [0015]. [0021]. [0062] packages processed separately according to their grade info. Inada: Col. 8, cameras start photographing. Images processed by a computer, judges bunch or bulge winding. discharge end of the conveyor has a transfer apparatus for transferring an empty tray onto the return conveyor. at the entrance end of the conveyor is mounted a transfer apparatus for transferring the empty tray from the return conveyor over to the conveyor. Cols. 8-9, tray emptied, then transferred over to the return conveyor and transferred, for a reuse purpose, from the return conveyor over to the conveyor).
Regarding Claim 6: Wu-Inada further teach: The method of claim 1, wherein the pallet diversion device comprises a first diversion device and a second diversion device arranged on the main line of the assembly line, and branch lines of the assembly line comprise a first branch line and a second branch line; wherein the controlling the pallet diversion device to divert the pallet to be recycled from the main line of the assembly line to a branch line of the assembly line, comprises: (Wu: [0004]-[0005], [0015], [0021], [0062]. Inada: Col. 6, Col. 8, Cols. 8-9)
controlling the first diversion device to divert the first pallet to be recycled from the main line of the assembly line to the first branch line of the assembly line; and controlling the second diversion device to divert the second pallet to be recycled from the main line of the assembly line to the second branch line of the assembly line (Wu: [0004] during boxing and palletizing the packages, the packages need to be inspected for weight and appearance. [0005] fully automatic intelligent packaging system for chemical fiber DTY spindles, which includes a spindle entry track and a serpentine track. An intelligent inspection and classification system. inspect the weight and dyeing grade of spindles of different batches and models, classify, and grade spindles of different batches and models. [0015] weight detection of roll, appearance detection of roll, and grade info based on these detections. [0021] roll with first grade is placed at first palletizing station and palletized as roll with first grade; roll with second grade placed a second palletizing station and palletized as roll with second grade. [0062] packages processed separately according to their grade info. Inada: Col. 6, conveyor for carrying the package on the tray. conveyor arranged on the upper stage of the frame. On the lower stage of the frame is installed a return conveyor for returning the tray. Col. 8, discharge end of the conveyor has a transfer apparatus for transferring an empty tray onto the return conveyor. at the entrance end of the conveyor is mounted a transfer apparatus for transferring the empty tray from the return conveyor over to the conveyor. Cols. 8-9, tray emptied, then transferred over to the return conveyor and transferred, for a reuse purpose, from the return conveyor over to the conveyor).
Regarding Claim 7: Wu-Inada further teach: The method of claim 6, wherein the pallet diversion device further comprises a third diversion device arranged on the second branch line, and the branch lines of the assembly line further comprise a third branch line; wherein the controlling the pallet diversion device to divert the pallet to be recycled from the main line of the assembly line to a branch line of the assembly line, further comprises: (Wu: [0004]-[0005], [0015], [0021], [0062]. Inada: Col. 6, Col. 8, Cols. 8-9)
controlling the third diversion device to divert the second pallet to be recycled from the second branch line to a pallet recycle location when a re-inspection result of the second pallet to be recycled indicates that the yarn spindle to be packaged on the second pallet to be recycled is a graded yarn spindle; or, controlling the third diversion device to divert the second pallet to be recycled from the second branch line to the third branch line to flow back from the third branch line to the main line of the assembly line when the re-inspection result of the second pallet to be recycled indicates that the yarn spindle to be packaged on the second pallet to be recycled is a non-graded yarn spindle (Wu: [0004]. [0005]. [0015]. [0021]. [0062]. Inada: Col. 6, conveyor for carrying the package on the tray. conveyor arranged on the upper stage of the frame. On the lower stage of the frame is installed a return conveyor for returning the tray. Col. 8, discharge end of the conveyor has a transfer apparatus for transferring an empty tray onto the return conveyor. at the entrance end of the conveyor is mounted a transfer apparatus for transferring the empty tray from the return conveyor over to the conveyor. Cols. 8-9, tray emptied, then transferred over to the return conveyor and transferred, for a reuse purpose, from the return conveyor over to the conveyor).
Regarding Claim 8: Claim 8 corresponds in scope to Claim 1 and is similarly rejected. The motivation for modification is the same as that provided in claim 1. Wu-Inada further teach: An electronic device comprised in a yarn spindle packaging system, wherein the electronic device communicates with an image acquisition device and a pallet diversion device respectively, comprising: (Wu: [0002] automatic roll stacking and packaging. [0023] system, conveyor, processor, controller, storage medium, control robot, palletizing, packaging and conveying devices to automatically palletize and package roll. Fig. 3: pallets 72, yarn spindles 71, shows packaging system for yarn spindles on pallets)
at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores an instruction executable by the at least one processor, and the instruction, when executed by the at least one processor, enables the at least one processor to execute (Wu: [0023] system, conveyor, processor, controller, storage medium, control robot, palletizing, packaging and conveying devices to automatically palletize and package roll).
Regarding Claim 9: Claim 9 corresponds in scope to Claim 2 and is similarly rejected.
Regarding Claim 10: Claim 10 corresponds in scope to Claim 3 and is similarly rejected.
Regarding Claim 11: Claim 11 corresponds in scope to Claim 4 and is similarly rejected.
Regarding Claim 13: Claim 13 corresponds in scope to Claim 6 and is similarly rejected.
Regarding Claim 14: Claim 14 corresponds in scope to Claim 7 and is similarly rejected.
Regarding Claim 15: Wu-Inada further teach: A non-transitory computer-readable storage medium storing a computer instruction thereon, wherein the computer instruction is used to cause a computer to execute the method of claim 1 (Wu: [0023] system, conveying device, processor, control device, readable storage medium, controlling the roll-online robot, the palletizing device, the packaging device and the conveying device to automatically palletize and package the roll).
Claim(s) 5, 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (CN 111086693 A) and Inada et al. (US 5,359,408 A), and further in view of Seo (US 2024/0193759 A1, “Seo”).
Regarding Claim 5: Wu-Inada further teach: The method of claim 4, wherein the defect detection network [detects the yarn spindles one by one, and determines a defect detection result] (Wu: [0005] fully automatic intelligent packaging system for chemical fiber DTY spindles. inspect the weight and dyeing grade of spindles of different batches and models, classify, and grade spindles. [0015] weight, appearance, and grade info based on these detections. [0016] grade info of each package one by one. [0062] packages processed separately according to grade info (winding, storage might cause loose threads, intactness issues). [0069] appearance detection modules. Inada: Col. 8, cameras start photographing. Images processed by a computer, judges bunch or bulge winding. Cols. 8-9, tray emptied, then transferred over to the return conveyor and transferred, for a reuse purpose, from the return conveyor over to the conveyor).
However, Wu-Inada do not explicitly teach: wherein the defect detection network comprises a first network layer, a second network layer and a third network layer; the first network layer is used to combine a channel attention mechanism with a spatial attention mechanism to perform feature extraction on the yarn spindle image to obtain K feature representation graphs in different scales; wherein K≥2 and K is an integer; the second network layer is used to perform feature fusion based on the K feature representation graphs to obtain K fused feature graphs; wherein the K fused feature graphs correspond to the K feature representation graphs one by one; and the third network layer is used to obtain a defect detection result based on the K fused feature graphs; wherein the defect detection result is used to indicate whether the yarn spindle image has a defect feature.
Seo teaches: wherein the defect detection network comprises a first network layer, a second network layer and a third network layer; ([0130] deep neural network (DNN), neural network that includes an input layer, an output layer, and a plurality of hidden layers)
the first network layer is used to combine a channel attention mechanism with a spatial attention mechanism to perform feature extraction on the yarn spindle image to obtain K feature representation graphs in different scales; wherein K≥2 and K is an integer; ([0084] learning the images expressing the shape and color of the object using deep learning or machine learning, classifying or learning the features of the image data on its own, and may specify the type of unit process by classifying and detecting the objects)
the second network layer is used to perform feature fusion based on the K feature representation graphs to obtain K fused feature graphs; wherein the K fused feature graphs correspond to the K feature representation graphs one by one; and ([0085]-[0089] When detecting the object, generate training data by preprocessing image data of object. training data labeled with assembly state, defect state, and unit process type info. classifier model learned and applied to the machine learning model. image data collected through camera preprocessed, classifier model used to detect object, presence or absence of defect, completion or non-completion of assembly)
the third network layer is used to obtain a defect detection result based on the K fused feature graphs; wherein the defect detection result is used to indicate whether the yarn spindle image has a defect feature ([0110]-[0114] FIG. 3, machine learning model detect part A, specify the unit process type A. completion or non-completion of specified unit process A is checked. collect execution data of unit process A by evaluating, in real time, time required until specified unit process A is completed and presence or absence of defect. may detect and recognize that the object has changed. collect execution data by evaluating, in real time, the completion or non-completion of the unit process B, which is specified as the changed object, the required time, and the presence or absence of defect).
Wu-Inada and Seo are analogous art to the claimed invention since they are from the similar field of assembly line optimization via computer vision and artificial intelligence. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Wu-Inada with the aspects of Seo to create, with a reasonable expectation for success, a pallet recycling method that includes a defect detection network with first, second, and third network layers, where the layers combine a channel attention mechanism with a spatial attention mechanism to perform feature extraction on the yarn spindle image, perform feature fusion based on the feature representation graphs, and obtain a defect detection result based on the fused feature graphs, wherein the result is used to indicate whether the yarn spindle image has a defect feature. The motivation for modification would have been to improve the efficiency of the system by using machine learning to continuously learn the images of the object and determine the presence or absence of defect (Seo, [0083]-[0084]), which reduces the error rate and overall time required for process execution (Seo, [0104]).
Regarding Claim 12: Claim 12 corresponds in scope to Claim 5 and is similarly rejected. The motivation for modification of claim 5 is similarly applied to claim 12.
Conclusion
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