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 .
DETAILED ACTION
The present application, filed on or after March 13, 2013, is being examined under the first inventor to file provisions of the AIA .
1. This action is responsive to communications: Application filed on 4/22/2024, and Drawings filed on 4/22/2024.
2. Claims 1–6, 8, 10 are pending in this case. Claim 1, 8, 10 are independent claims.
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 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.
Claim Rejections - 35 U.S.C. § 101
35 U.S.C. § 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4, 8, 10 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
As to claim 1:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a machine.
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “perform inference on the target included in the configuration data; perform inference on the target included in the data in at least a portion of the data;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “determine whether inference on the target included in the configuration data has succeeded or failed for each piece of the data constituting the configuration data;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “perform inference on the target based on the configuration data and a result of performing inference on the target included in the configuration data as inference on the target included in the data for which inference on the target included in the configuration data has succeeded;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “and perform inference on the target based on a result of performing inference on the target included in the data as inference on the target included in the data for which inference on the target included in the configuration data has failed.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
No, the limitation “a memory configured to store instructions; and one or more processors configured to execute the instructions to: generate configuration data configured using a plurality of pieces of data, at least a portion of which including an inference target;” is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
No, the limitation “a memory configured to store instructions; and one or more processors configured to execute the instructions to: generate configuration data configured using a plurality of pieces of data, at least a portion of which including an inference target;” is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP §§ 2106.04(d), 2106.05(g). (“The collecting step is recited at a high level of generality (i.e., as a general means of gathering network traffic data for use in the comparison step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.”).
As to claim 2:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a machine. (apparatus, system)
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “perform inference on the target included in the second configuration data, wherein determine whether inference on the target included in the second configuration data has succeeded or failed for each piece of the data constituting the second configuration data;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “perform inference on the target based on the second configuration data and a result of performing inference on the target included in the second configuration data as inference on the target included in the data for which inference on the target included in the second configuration data has succeeded;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “and perform inference on the target based on a result of performing inference on the target included in the data as inference on the target included in the data for which inference on the target included in the second configuration data has failed.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
No, the limitation “generate second configuration data configured using a plurality of pieces of the data for which inference on the target included in the configuration data has failed;” is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
No, the limitation “generate second configuration data configured using a plurality of pieces of the data for which inference on the target included in the configuration data has failed;” is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP §§ 2106.04(d), 2106.05(g). (“The collecting step is recited at a high level of generality (i.e., as a general means of gathering network traffic data for use in the comparison step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.”).
As to claim 3:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a machine. (apparatus, system).
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “switch an operation in at least one of the generation of configuration data, the inference on the target in the configuration data, the inference on the target included in the data in at least a portion of the data, and the inference on the targe based on the configuration data and the result of performing inference on the target based on an inference situation in at least one of the inference on the target in the configuration data and the inference on the target included in the data in at least a portion of the data.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
The analysis of the parent claim is incorporated.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
The analysis of the parent claim is incorporated.
v1.2 7/9/2024
As to claim 4:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a machine. (apparatus, system).
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “wherein the inference situation is inference accuracy or inference speed, and switching of an operation is a change of a threshold used for determining whether inference on the target included in the configuration data has succeeded or failed, a change of a model used for inference, a change of a size of the configuration data, or a combination thereof.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
The analysis of the parent claim is incorporated.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
The analysis of the parent claim is incorporated.
Claims 8 is the method claim and is rejected for the same reason as claim 1.
Claim 10 is the media claim and is rejected for the same reason as claim 1.
Claims 2, 4 would be allowable if rewritten or amended to overcome the 101 and 112 rejections.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1-8, 10 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 claims the limitation of “1. An information processing device comprising: a memory configured to store instructions; and one or more processors configured to execute the instructions to: generate configuration data configured using a plurality of pieces of data, at least a portion of which including an inference target; perform inference on the target included in the configuration data; perform inference on the target included in the data in at least a portion of the data; determine whether inference on the target included in the configuration data has succeeded or failed for each piece of the data constituting the configuration data; perform inference on the target based on the configuration data and a result of performing inference on the target included in the configuration data as inference on the target included in the data for which inference on the target included in the configuration data has succeeded; and perform inference on the target based on a result of performing inference on the target included in the data as inference on the target included in the data for which inference on the target included in the configuration data has failed.”
With regard to the limitation “perform inference on the target included in the data in at least a portion of the data.” It is unclear what constitutes “the data in at least a portion of the data”. It is unclear what is the relationship between the first data and second data. It is unclear what the first data is referring to. It is unclear whether it is referring to the “configuration data” or “the plurality pieces of data”.
With regard to the limitation “determine whether inference on the target included in the configuration data has succeeded or failed for each piece of the data constituting the configuration data.” It is unclear whether the inferencing is referring to “perform inference on the target included in the data in at least a portion of the data” or the “perform inference on the target included in the data in at least a portion of the data”. It is unclear what is the relationship and difference between the two inferences.
For the purpose of a compact prosecution the inference is referring to “perform inference on the target included in the data in at least a portion of the data”.
Claim 8 is rejected for the same reason as claim 1.
Claim 10 is rejected for the same reason as claim 1.
Claims 2, 4 would be allowable if rewritten or amended to overcome the 101 and 112 rejections.
Claims 5 would be allowable if rewritten or amended to overcome the 112 rejection.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 6, 8, 10 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Cai, Pub. No.: CN 112883973 A.
With regard to claim 1:
Cai discloses an information processing device comprising: a memory configured to store instructions; and one or more processors configured to execute the instructions to: generate configuration data configured using a plurality of pieces of data, at least a portion of which including an inference target(see fig. 3 and 4 wherein the inference targets are license plates from a plurality of license plate images, “In some embodiments, license plate text image comprises a plurality of each license plate text image corresponding to a detection frame, for example, for the license plate image shown in FIG. 4, using the neural network for processing, can obtain two detection frame shown in FIG. 5, in FIG. 5; the second detection frame 501 and the third detection frame 502 in the image is two license plate text, the content of the second detection frame 501 is digital " 7356 ", the content of the third detection frame 502 is letter " TNJ ". In some embodiments, the license plate text image comprises a plurality of license plate text images in the same row and are arranged at intervals, each license plate text image corresponding to a detection frame, for example, in FIG. 5, the second detection frame 501 and the third detection frame 502 in the image representation in the two license plate text in the same row; the second detection frame 501 and the third detection frame 502 are arranged at intervals, namely the second detection frame 501 and the third detection frame 502 is provided with a second region of the image 503. Therefore, the present disclosure can identify the license plate number in the same row of different positions.”); perform inference on the target included in the configuration data (the system performs inference on the target such as license plate in the configuration data “In some embodiments of the present disclosure, the license plate text image comprises a plurality of condition, can be text recognition to a plurality of license plate text respectively, obtaining a plurality of license plate text corresponding to the text recognition result, then the plurality of license plate text corresponding to the text recognition result to combine to obtain the license plate text. In some embodiments of the present disclosure, the license plate text image comprises a plurality of, and a plurality of license plate text images are in the same row and the interval is set under the condition that the plurality of license plate text respectively in the same row for text recognition, obtaining a plurality of license plate text corresponding to the text recognition result; For example, referring to FIG. 5, the second detection frame 501 and the third detection frame 502 represented by two license plate text image in the same row, and the two license plate text images are set at intervals, at this time, can the second detection frame 501 and the third detection frame 502 represents the two license plate text to text recognition, to obtain the digital " 7356 " and letter " TNJ ", then, the number " 7356 " and letter " TNJ " to combine, obtaining the license plate text " 7356TNJ ".”); perform inference on the target included in the data in at least a portion of the data (the system performs inference on the target which is license plate: “The method comprises the following steps: performing text recognition to at least one license plate text image to obtain the license plate number text. Some embodiments of the present disclosure, can use optical character recognition (OCR) method for text recognition of at least one license plate text image, OCR refers to the process of using character recognition method to translate the shape into computer text process ; namely, analyzing and processing the image file of the text data, obtaining the process of character and layout information. in some embodiments of the present disclosure, it also can utilize pre-trained text recognition model for text recognition of at least one license plate text, illustratively, text recognition model can be region convolutional neural network (Regions with Convolutional Neural Network, RCNN) and so on.”); determine whether inference on the target included in the configuration data has succeeded or failed for each piece of the data constituting the configuration data (see fig. 6 wherein the system determines whether the inference of the configuration data is successful or not, “Step 604: judging whether the angle detection model after adjusting the network parameter value satisfies the first training end condition, if not, then re-executing step 601 to step 604; if yes, executing step 605. In the embodiment of the present disclosure, the first training end condition can be the iteration times when the training angle point detection model reaches the first set times, or loss of the network parameter value after adjusting the corner of the detection model is less than the first set loss; Here, the first setting times and the first setting loss can be preset.”); perform inference on the target based on the configuration data and a result of performing inference on the target included in the configuration data as inference on the target included in the data for which inference on the target included in the configuration data has succeeded (the inference is done by adjusting the learning model, “Step 604: judging whether the angle detection model after adjusting the network parameter value satisfies the first training end condition, if not, then re-executing step 601 to step 604; if yes, executing step 605. In the embodiment of the present disclosure, the first training end condition can be the iteration times when the training angle point detection model reaches the first set times, or loss of the network parameter value after adjusting the corner of the detection model is less than the first set loss; Here, the first setting times and the first setting loss can be preset. Step 605: and taking the angle detection model after adjusting the network parameter value as the corner detection model finished by training. In the actual application, step 601 to step 605 can be realized by the processor in the electronic device, the processor can be an ASIC, DSP, DSPD, PLD, FPGA, CPU, controller, microcontroller, microprocessor is at least one. It can be seen that in the embodiment of the present disclosure, by pre-training the angular point detection model, can make the training corner of the detection model can more accurately corner the information of the license plate, so as to correct the initial image of the license plate. In some embodiments of the present disclosure, the neural network is based on the license plate of the second sample image set and the second sample image set of the marked license plate text image training; the marked license plate text image of the second sample image set is the marked license plate text image of each sample image in the second sample image set. In the embodiment of the present disclosure, the second sample image set may include a plurality of sample images, in some embodiments, for each sample image in the second sample image set, can be pre-marked the real license plate text line area, namely obtaining the sample image of the marked license plate text. Hereinafter, the training process of the neural network is illustrated by the accompanying drawings.”.) and perform inference on the target based on a result of performing inference on the target included in the data as inference on the target included in the data for which inference on the target included in the configuration data has failed (the inference is done by reperform the training steps when the inference on the target included in the configuration data has failed, “Step 604: judging whether the angle detection model after adjusting the network parameter value satisfies the first training end condition, if not, then re-executing step 601 to step 604; if yes, executing step 605. In the embodiment of the present disclosure, the first training end condition can be the iteration times when the training angle point detection model reaches the first set times, or loss of the network parameter value after adjusting the corner of the detection model is less than the first set loss; Here, the first setting times and the first setting loss can be preset.”).
With regard to claim 6:
Cai discloses The information processing device according to claim 1, wherein the data is an image of two-dimensional data, and the one or more processors are further configured to execute the instructions to: generate a configuration image in which a plurality of images are arranged on a two-dimensional plane(see fig. 2 to 4 wherein a plurality of images are arranged on a two dimensional plane: “In some embodiments, the license plate text image comprises a plurality of license plate text images in the same row and are arranged at intervals, each license plate text image corresponding to a detection frame, for example, in FIG. 5, the second detection frame 501 and the third detection frame 502 in the image representation in the two license plate text in the same row; the second detection frame 501 and the third detection frame 502 are arranged at intervals, namely the second detection frame 501 and the third detection frame 502 is provided with a second region of the image 503. Therefore, the present disclosure can identify the license plate number in the same row of different positions.”); execute an object detection task as inference on the target included in a configuration image (the system performs inference on the target such as license plate in the configuration data “In some embodiments of the present disclosure, the license plate text image comprises a plurality of condition, can be text recognition to a plurality of license plate text respectively, obtaining a plurality of license plate text corresponding to the text recognition result, then the plurality of license plate text corresponding to the text recognition result to combine to obtain the license plate text. In some embodiments of the present disclosure, the license plate text image comprises a plurality of, and a plurality of license plate text images are in the same row and the interval is set under the condition that the plurality of license plate text respectively in the same row for text recognition, obtaining a plurality of license plate text corresponding to the text recognition result; For example, referring to FIG. 5, the second detection frame 501 and the third detection frame 502 represented by two license plate text image in the same row, and the two license plate text images are set at intervals, at this time, can the second detection frame 501 and the third detection frame 502 represents the two license plate text to text recognition, to obtain the digital " 7356 " and letter " TNJ ", then, the number " 7356 " and letter " TNJ " to combine, obtaining the license plate text " 7356TNJ ".”); and execute an image classification task as inference on the target included in an image (“Exemplary, when the vehicle detection model is a target detection model based on the deep learning, the vehicle detection task of the vehicle detection model can be divided into the following two sub-tasks: target classification and target location. the target classification task is responsible for judging whether there is vehicle in the input image or the selected image area (Provision); outputting a series of label with score indicating the possibility of the vehicle appearing in the image or the selected image area. The target positioning task is responsible for determining the position and range of the vehicle in the image or the selected image area, the surrounding box of the output object, or the object centre, or the closed boundary of the object, generally using a square detection frame to represent the position information of the vehicle.”).
Claim 8 is rejected for the same reason as claim 1.
Claim 10 is rejected for the same reason as claim 1.
Claim Rejections - 35 USC § 103
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.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cai, and in view of Phoon, Pub. No.: 20180101633 A1.
With regard to claim 3:
Cai does not disclose The information processing device according to claim 1, wherein the one or more processors are further configured to execute the instructions to: switch an operation in at least one of the generation of configuration data, the inference on the target in the configuration data, the inference on the target included in the data in at least a portion of the data, and the inference on the targe based on the configuration data and the result of performing inference on the target based on an inference situation in at least one of the inference on the target in the configuration data and the inference on the target included in the data in at least a portion of the data.
However Phoon disclose the aspect wherein the one or more processors are further configured to execute the instructions to: switch an operation in at least one of the generation of configuration data, the inference on the target in the configuration data, the inference on the target included in the data in at least a portion of the data, and the inference on the targe based on the configuration data and the result of performing inference on the target based on an inference situation in at least one of the inference on the target in the configuration data and the inference on the target included in the data in at least a portion of the data (paragraph 72 and 73: “At step 512, the configuration bit stream may be ready to be loaded onto the programmable integrated circuit. Therefore, the configuration bit stream may be output to configuration data loading equipment 54 of FIG. 2 or directly to configuration device 40 of FIG. 2. The configuration bit stream may then configure (or reconfigure) the programmable integrated circuit. The illustrative steps provided in FIG. 5 are merely illustrative. If desired, some steps may be omitted, while others may be repeated. The order of these steps may be altered in any desired way to generate a suitable set of configuration data. Some or all of these steps may be abstracted away from the user (e.g., designer), such that the user may not need to under the complexities associated with some or all of the steps.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Phoon to Cai so the system can switch the operation to generate configuration data, allow different method of generation of configuration data that would provide alternate configuration data for inference for greater data variety and allow verification through multiple different generation of configuration data.
Pertinent Arts
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chun, Pub. No.: 2022/0092319A1, A vehicle may include a camera; a storage; and a controller electrically connected to the camera and the storage. The controller may be configured to obtain a front image of the vehicle from the camera by controlling the camera, in a response to obtaining the front image, to identify image data corresponding to a license plate of a front vehicle positioned in front of the vehicle from the front image, to identify a decrease in a distance between the vehicle and the front vehicle based on the image data and reference distance information corresponding to at least one reference image data of at least one reference license plate stored in the storage, to identify a change in height of the license plate of the front vehicle based on the image data, and based on the decrease in the distance between the vehicle and the front vehicle and the change in height of the license plate of the front vehicle, to identify a speed bump located in front of the vehicle.
Chen, Pub. No.: US 20210295080 A1: A system and method for license plate recognition is provided in the present disclosure. The method may include obtaining an image including a license plate mounted on a vehicle, and identifying at least one feature point associated with the vehicle. The method may also include determining an approximate angle range within which a tilt angle of the license plate is located based on the at least one feature point, and determining the tilt angle of the license plate within the approximate angle range. The method may further include performing a tilt correction on the license plate based on the tilt angle of the license plate.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DI XIAO whose telephone number is (571)270-1758. The examiner can normally be reached 9Am-5Pm est M-F.
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/DI XIAO/Primary Examiner, Art Unit 2178