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
This is a Non-Final Office Action, in responses to Applicant’s RCE/amendments/remarks filed 05/04/2026. It is noted, the current Patent Application was filed 12/30/2025. It is noted, the current Patent Application filed 04/26/2022; is a Continuation of 16906224, filed 06/19/2020, now U.S. Patent # 11356601. Claim(s) 1-20 are pending. Claim(s) 1, 11 and 18 are independent claims. Claim 1 was previously presented. Claim(s) 11 and 18 are currently amended. Claim(s) 2-10, 12-17 and 19-20 were original.
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 05/04/2026 has been entered.
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.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 1-20 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over Claims 1-20 of U.S. Patent 11,356,601 issued 06/07/2022 to Patent Application 16/906,224 filed 06/19/2020 (hereinafter, “Patent ‘601”).
Although the conflicting claims are not identical, but they are not patentably distinct from each other because they are both exhibiting similar method/device/apparatus.... via “.... an image sensor and random access memory; wherein a unit operable to execute instructions and configured, via first data representative of attributes of an artificial neural network and second data representative of the instructions executable by the at least one processing unit, to implement matrix computations of the artificial neural network; and a controller coupled with the image sensor and the random access memory and configured to: write image data generated by the image sensor into the random access memory as an input to the artificial neural network, wherein writing the image data by the image sensor into the random access memory causes at least one processing unit to implement the matrix computations of the artificial neural network to generate an output of the artificial neural network responsive to the input; and generate, based on the output of the artificial neural network, third data representative of a description of an item or event captured in the image data...” in the BRI (Broadest Reasonable Interpretation); which is conceptually the same invention and/or a more specific version as US Patent ‘601 for:...an image sensor configured to generate image data of a field of view of the device; at least one processing unit configured to execute instructions having matrix operands; random access memory configured to store first data representative of weights of an artificial neural network and store second data representative of the instructions executable by the at least one processing unit to implement matrix computations of the artificial neural network using the first data representative of the weights of the artificial neural network; a transceiver configured to communicate with a computer system separate from the device; and a controller coupled with the transceiver, the sensor and the random access memory, wherein the controller is configured to write the image data into the random access memory as an input to the artificial neural network; wherein the at least one processing unit is further configured to execute the instructions represented by the second data stored in the random access memory to generate an output of the artificial neural network based at least in part on the first data and the image data stored in the random access memory; and wherein the controller is further configured to provide third data representative of a description of an item or event captured in the image data based on the output of the artificial neural network, and control the transceiver to provide the third data representative of the description to the computer system... [Claim 1 of Patent ‘601]…
Thus, they are both exhibiting similar method to perform an indication of a first update to a first replica of a document from a first computing device, … via first data representative of attributes of an artificial neural network and second data representative of the instructions executable by the at least one processing unit, to implement matrix computations of the artificial neural network; a controller coupled with the image sensor and the random access memory and configured to: write image data generated by the image sensor into the random access memory as an input to the artificial neural network, causing the at least one processing unit to implement the matrix computations of the artificial neural network to generate an output of the artificial neural network responsive to the input; and generate, based on the output of the artificial neural network, third data representative of a description of an item or event captured in the image data....
Please noted: A terminal disclaimer may be effective to overcome a provisional obviousness-type double patenting rejection over a pending application (37 CFR 1.321(b) and (c)). The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
The Claims are comparing as following:
Claim(s) 1-20 of current application and the Patent ‘601 are compared as following:
Current Application
Patent ‘601
Claim(s) 1-20
Claim(s) 1-20
[Claim 1 of 17/729,849] comparing to
A device, comprising: an image sensor; random access memory; at least one processing unit operable to execute instructions and configured, via
first data representative of attributes of an artificial neural network
and second data representative of the instructions executable by the at least one processing unit, to implement matrix computations of the artificial neural network;
a controller coupled with the image sensor and the random access memory and configured to: write image data generated by the image sensor into the random access memory as an input to the artificial neural network, wherein writing the image data by the image sensor into the random access memory causes
at least one processing unit to implement the matrix computations of the artificial neural network to generate an output of the artificial neural network responsive to the input; and generate, based on the output of the artificial neural network, third data representative of a description of an item or event captured in the image data...(See claim 1)
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[Claim 11 of 17/729,849] comparing to
A method, comprising: configuring a device, having at least one processing unit operable to execute instructions to implement matrix computations of an artificial neural network, by storing in a memory: first data representative of attributes of the artificial neural network;
and second data representative of the instructions executable by the at least one processing unit; generating, by an image sensor of the device, image data;
writing, by a controller coupled with the image sensor in the device, the image data into the memory as an input to the artificial neural network, causing the at least one processing unit to execute the instructions;
executing, by the at least one processing unit in response to the writing the image data into the memory, instructions to implement the matrix computations of the artificial neural network and generate an output of the artificial neural network responsive to the input; and generating, based on the output of the artificial neural network, third data representative of a description of an item or event captured in the image data... [Claim 11]
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[Claim 18 of 17/729,849] comparing to
An apparatus, comprising: a lens; an image sensor configured behind the lens to generate image data; memory configured to store data of an artificial neural network;
at least one processing unit configured to execute instructions configured to implement computations of the artificial neural network having the data stored in the memory;
and wherein the image sensor is configured to write the image data into the memory as an input to the artificial neural network;
wherein the at least one processing unit is configured to execute, in response to the image sensor writing the image data into the memory, the instructions to implement the computations of the artificial neural network to generate an output responsive to the input; and wherein the apparatus is configured to generate a description of an item or event captured in the image data...[Claim 18]
Also, Claims(2-10 and 12-17 and19-20) of 17/729,849
[Claim 1 of Patent ‘601]
A device, comprising: an image sensor configured to generate image data of a field of view of the device; at least one processing unit configured to execute instructions having matrix operands;
random access memory configured to store first data representative of weights of an artificial neural network
and store second data representative of the instructions executable by the at least one processing unit to implement matrix computations of the artificial neural network using the first data representative of the weights of the artificial neural network;
a transceiver configured to communicate with a computer system separate from the device; and a controller coupled with the transceiver, the sensor and the random access memory, wherein the controller is configured to write the image data into the random access memory as an input to the artificial neural network;
wherein the at least one processing unit is further configured to execute the instructions represented by the second data stored in the random access memory to generate an output of the artificial neural network based at least in part on the first data and the image data stored in the random access memory;
––
and wherein the controller is further configured to provide third data representative of a description of an item or event captured in the image data based on the output of the artificial neural network, and control the transceiver to provide the third data representative of the description to the computer system....(See Claim 1)
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[Claim 1 of Patent ‘601]
A device, comprising: an image sensor configured to generate image data of a field of view of the device; at least one processing unit configured to execute instructions having matrix operands;
random access memory configured to store first data representative of weights of an artificial neural network
and store second data representative of the instructions executable by the at least one processing unit to implement matrix computations of the artificial neural network using the first data representative of the weights of the artificial neural network;
a transceiver configured to communicate with a computer system separate from the device;
and a controller coupled with the transceiver, the sensor and the random access memory, wherein the controller is configured to write the image data into the random access memory as an input to the artificial neural network;
wherein the at least one processing unit is further configured to execute the instructions represented by the second data stored in the random access memory to generate an output of the artificial neural network based at least in part on the first data and the image data stored in the random access memory; and wherein the controller is further configured to provide third data representative of a description of an item or event captured in the image data based on the output of the artificial neural network, and control the transceiver to provide the third data representative of the description to the computer system....(See Claim 1)
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[Claim 1 of Patent ‘601]
A device, comprising: an image sensor configured to generate image data of a field of view of the device; at least one processing unit configured to execute instructions having matrix operands;
random access memory configured to store first data representative of weights of an artificial neural network
and store second data representative of the instructions executable by the at least one processing unit to implement matrix computations of the artificial neural network using the first data representative of the weights of the artificial neural network; a transceiver configured to communicate with a computer system separate from the device;
and a controller coupled with the transceiver, the sensor and the random access memory, wherein the controller is configured to write the image data into the random access memory as an input to the artificial neural network; wherein the at least one processing unit is further configured to execute the instructions represented by the second data stored in the random access memory to generate an output of the artificial neural network based at least in part on the first data and the image data stored in the random access memory; and wherein the controller is further configured to provide third data representative of a description of an item or event captured in the image data based on the output of the artificial neural network, and control the transceiver to provide the third data representative of the description to the computer system....(See Claim 1)
Compares to Claim(s) 1-20 of Patent ‘601
Allowable Subject Matter
Claim(s) 1-20 would be allowable if filling the “Terminal Disclaimer” to remedy the nonstatutory double patenting rejection.
Reason for Allowance
Under the broadest reasonable interpretation of the claimed limitation which is consistence with the Applicant's Specification, the prior arts of recorded when taken individually or in combination do not expressly teach or render obvious the limitations recited in claim(s) 1, 11 and 18 when taken in the context of the claims as a whole, especially the concept of, … “comprising: an image sensor; random access memory; wherein the processing unit operable to execute instructions and configured, via first data representative of attributes of an artificial neural network and second data representative of the instructions executable by the at least one processing unit, to implement matrix computations of the artificial neural network; wherein the image sensor and the random access memory and configured to: write image data generated by the image sensor into the random access memory as an input to the artificial neural network, wherein writing the image data by the image sensor into the random access memory causes the at least one processing unit to implement the matrix computations of the artificial neural network to generate an output of the artificial neural network responsive to the input; and generate, based on the output of the artificial neural network, third data representative of a description of an item or event captured in the image data...” as claimed and armaments and remarks filed with the RCE 05/04/2026 and supported in the current specifications USPGPUB 20220256077 A1 in Para(s) 111-119.
In addition, neither a reference (i.e., Snowden (20200241716) in view of Hallman (11398094) uncovered that would have provided a basis of evidence for asserting a motivation, nor one of ordinary skilled in the art before the effective filing date of the claimed invention, would have combined them to arrive at the present invention as recited in the context of independent claim(s) 1, 11 and 18 as a whole.
Thus, claim(s) 1, 11 and 18 is/are allowed over the prior arts of record. Also, dependent claim(s) 2-10, 12-17 and 19-20, are also allowable due to its dependency of independent claim(s) 1, 11 and 1 ( assuming the “Terminal Disclaimer” will be filed in the next communication). [see the remarks filed with the RCE dated 05/04/2026]
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Response to Arguments
In responses to Applicant’s arguments, [see the Applicant’s Amendments and remarks filed with the RCE dated 05/04/2006]; with respect to the rejection(s) of claim(s) 1-20 under 101 and 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of newly amended Claim(s) 11 and 18 (Currently Amended) and claims 1 (Previously Presented) and (See the above rejection for details) and further view of the “Reason for Allowance” above for details.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kwant (“US 20220101071 A1” Continuation to 16/817,708 filed 03/13/2020, discloses Traffic signal devices includes camera, wherein the computer system using the transceiver to the transmission of data signals between two or more electronic devices......[Para(s) Para(s) 14 and 34, 37 and 41].
Sriram et al (“US 20200302161 A1” filed 06/09/2020, discloses ROI-based occupancy detection to determine whether particular parking spots are occupied by leveraging image data from image sensors, such as cameras. These approaches may also include multi-sensor object tracking using multiple sensors that are distributed across an area that leverage both image data and spatial information regarding the area, to provide precise object tracking across the sensors. Further approaches relate to various architectures and configurations for smart area monitoring systems, as well as visualization and processing techniques. For example, as opposed to presenting video of an area captured by cameras, 3D renderings may be generated and played from metadata extracted from sensors around the area...[Para(s) 5-8].
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/QUOC A TRAN/Primary Examiner, Art Unit 2145
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