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 .
Response to Amendment
The Amendment filed 05/15/2026 in response to the Non-Final Office Action mailed 02/17/2026 has been entered.
Claims 1-20 are currently pending in U.S. Patent Application No. 18/617,162 and an Office action on the merits follows.
Response to Double Patenting Rejections
Applicant’s remarks at page 9 do not explicitly traverse Double Patenting rejections set forth in the 02/17/2026 Non-Final Office Action, but instead request holding in abeyance such rejections until agreement on the scope of allowable claims enables evaluation of the same. Examiner is obligated to present early, and maintain where applicable, all pertinent grounds of rejection and avoid any piecemeal Examination. See e.g. MPEP 2173.06 and 707.07(g). See also MPEP 1205.02 regarding how any request to hold rejections in abeyance (in the context of Appeal Brief Content) may not meet the requirements of 37 CFR 41.37(c)(1)(iv). Examiner maintains that obvious modification to claims of reference warrants those Double Patenting rejection(s) previously presented and reproduced below, and requests Applicant’s filing of a Terminal Disclaimer in the interest of compact prosecution.
Response to Arguments/Remarks
Applicant's arguments filed 05/15/2026 have been fully considered but they are not persuasive. More specifically Applicant’s remarks assert that Sun fails to fairly disclose at least two residual blocks associated with a first downsampling factor, since those disclosed residual blocks of Sun are allegedly not ‘associated with’ factor s between the HR and LR images of Sun. Reproduced from Applicant’s remarks:
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In response Examiner identifies that permissible interpretation of the language “associated with”, merely requires that the residual blocks and the factor between HR and LR be connected/related/associated broadly – but fails to impose any constraints on ‘how’ e.g. where the ResBlocks are housed relative to any other/additional model/network components used in accomplishing a scaling from HR to LR. The fact that both a factor between HR and LR, and the ResBlocks are disclosed/suggested in Sun, is sufficient for finding the two elements are “associated with” each-other broadly and as required by the claim(s). Stated differently, no explicitly recited language limits ‘how’ the two must be connected, only that they be connected/ related/associated broadly. Applicant’s remarks point to various relationships between the components of Sun and conclude that each/all of these evidence against the required ‘associated with’ language, but remarks fail to articulate exactly how the claim as recited requires the elements in question to be related. The language in question is interpreted under a plain meaning reading as required in MPEP §§ 2173.01 and 2111.01, not inconsistent with Applicant’s Specification, but also not so as to read limitations from the Specification into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). If Applicant wishes to impose additional constraints by means of explicitly recited limitations, more precise than the current language ‘associated with’, amendment may be made to that affect. Otherwise, Applicant’s remarks fail to persuasively establish how a broad connection/relation/ association between the ResBlocks of Sun and factor between HR and LR fails to satisfy the requirements of the currently recited language.
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 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) 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 www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the grounds of nonstatutory double patenting as being unpatentable and/or obvious over one or more claims of:
U.S. Patent No. 11,948,271 B2 to parent application 17/133,206.
In further view of Sun et al. “Learned Image Downscaling for Upscaling using Content Adaptive Resampler” (attached PTO-892 NPL Citation No. V).
Although the claims at issue are not identical, they are not patentably distinct from each other because claims of reference at least render obvious independent claim(s) of the instant application, in further view of the following reasons/considerations:
• Instant claims and claims of reference recite common subject matter, and recite the open ended transitional phrase “comprising” which does not preclude any additional elements recited by claims of reference – see the limitation mappings/table presented below;
• Language/terminology of instant claim(s) constituting minor/slight variations from the claims of reference, if/where present, require interpretations under Broadest Reasonable Interpretation and/or plain meaning definitions (MPEP 2173 and 2111) equivalent to/met by language of the reference claims in view of that corresponding/shared Specification. While the disclosure of reference may not be used as prior art (Double Patenting concerns the claims of reference), portions of the specification which provide support for reference claims may also be examined and considered when addressing the scope of claim(s) of reference and the issue of whether an instant claim defines an obvious variation or falls within the scope of an invention claimed in the claim(s) of reference. See MPEP 804 with reference to In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970).
• Whereby element(s) of instant claim(s) otherwise not present explicitly in corresponding reference claim(s) (see * in the table below – i.e. limitations describing those residual blocks, but only in a manner wherein e.g. a skip connection/alternate function path is added/summed with the output of a convolutional layer stack (see Fig. 4 mappings to residuals 448 and 378 and summation operations that follow)), correspond(s) to known residual block characteristics and/or disclosure as identified in prior art of record to include e.g. Sun et al. “Learned Image Downscaling for Upscaling using Content Adaptive Resampler”. See also well-known literature He et al. “Deep Residual Learning for Image Recognition” (2016). It would have been obvious to a person of ordinary skill in the art, before the effective filing date, to modify claims of reference so as to further describe one or more residual blocks as recited and evidenced by Sun, the motivation as similarly taught/suggested therein and/or readily recognized by POSITA that those characteristics of a residual block allow for a faster and more stable convergence during training since the network is forced to learn only the residual/avoid vanishing gradients in back-propagation (particularly for deeper networks), and similar to that use in ResamplerNet of Sun, may allow for modeling the context of the input image.
Instant Claims
Claims of Reference US 11,948,271 B2
Claim 1
A computer-implemented method for training a neural network to downsample images in a video encoding pipeline, the method comprising:
Claim 1
A computer-implemented method for training a neural network to downsample images in a video encoding pipeline, the method comprising:
executing a first convolutional neural network on a first source image having a first resolution to generate a first downsampled image, wherein the first convolutional neural network includes at least two residual blocks associated with a first downsampling factor;
executing a first convolutional neural network on a first source image having a first resolution to generate a first downsampled image, wherein the first convolutional neural network includes at least two residual blocks;
executing an upsampling algorithm on the first downsampled image to generate a first reconstructed image having the first resolution;
executing an upsampling algorithm on the first downsampled image to generate a first reconstructed image having the first resolution;
computing a first reconstruction error based on the first reconstructed image and
the first source image; and
computing a first reconstruction error based on the first reconstructed image and the first source image; and
updating at least one parameter of the first convolutional neural network based on the first reconstruction error to generate a trained convolutional neural network; wherein
updating at least one parameter of the first convolutional neural network based on the first reconstruction error to generate a trained convolutional neural network.
a residual block comprises a portion of the first convolutional neural network that maps the input of the residual block to a residual and then adds the residual to a function of the input of the residual block to generate the output of the residual block; and wherein
*see bullet 3 above re. Obviousness type DP in view of characteristics common to residual blocks and as further evidenced in e.g. Sun et al. “Learned Image Downscaling for Upscaling using Content Adaptive Resampler” Fig. 1 light blue ResBlock illustrating that summation operation following output from conv/LeakyReLU/scale stack
each downsampled image has a resolution that is lower than a resolution of a corresponding source image by the first downsampling factor.
*see bullet 2 above, a downsampling factor is arguably inherent, if not at least implicit in view of recited “to generate a downsampled image” – it is necessarily downsampled by some measure/ factor, and the limitation in question serves only to establish a name for said factor
Claim 9
A computer-implemented method for downsampling images, the method comprising:
Claim(s) 21-22
A computer-implemented method for downsampling images, the method comprising:
executing a first trained convolutional neural network on a first source image having a first resolution to generate a first downsampled image having a second resolution that is lower than the first resolution;
executing a first trained convolutional neural network on a first source image having a first resolution to generate a first downsampled image having a second resolution that is lower than the first resolution,
wherein the first trained convolutional neural network includes at least two residual blocks associated with a first downsampling factor;
wherein the first trained convolutional neural network includes at least two residual blocks and is associated with a first downsampling factor.
wherein a residual block comprises a portion of the first trained convolutional neural network that maps the input of the residual block to a residual and then adds the residual to a function of the input of the residual block to generate the output of the residual block, and
See * Above re. corresponding limitation in Claim 1
wherein the at least two residual blocks include an upsampling residual block that is associated with a numerator of a resampling fraction and a downsampling residual block that is associated with a denominator of the resampling fraction.
Claim 22 (further limiting 21)
wherein the at least two residual blocks include an upsampling residual block that is associated with a numerator of a resampling fraction and a downsampling residual block that is associated with a denominator of the resampling fraction.
Dependent claims correspond to those as identified below in a more concise mapping, and for the case of CRM claim(s) 15-20, these claims are unpatentable over claims of reference in view of Obviousness type Double Patenting procedures as they relate to system/CRM and method claims of congruent scopes. It would have been obvious to a person of ordinary skill in the art, before the effective filing date, to modify congruent method claim(s) (22) of reference so as to be implemented by one or more generic non-transitory computer readable medium, the motivation being as readily recognized by POSITA that such medium embodiments may serve to facilitate product/software distribution in a manner characterized by a reasonable expectation of success.
Instant application
Claims of Reference
Claim(s) 2-8
Claim(s) 2-8 respectively
Claim(s) 10/16
Claim 23
Claim(s) 11/17
Claim 24
Claim(s) 12/18
Claim 25
Claim(s) 13/19
Claim 26
Claim(s) 14/20
Claim 27
Claim 15 CRM congruent to instant claim 9
Claim 22 – see corresponding method above for the case of instant claim 9
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(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.
1. Claim 1 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sun et al. “Learned Image Downscaling for Upscaling using Content Adaptive Resampler”.
As to claim 1, Sun discloses a computer-implemented method for training a neural network to downsample images in a video encoding pipeline, the method comprising:
executing a first convolutional neural network (ResamplerNet, Fig. 1) on a first source image having a first resolution (Fig. 1 input HR image) to generate a first downsampled image (Fig. 1 intermediate LR output between ResamplerNet and SRNet), wherein the first convolutional neural network includes at least two residual blocks (Fig. 1 light blue ResBlocks of ResamplerNet, 5 in total, page 6 section 4.1.2 Implementation details “5 residual blocks with each having features of 128 channels are used to model the context”) associated with a first downsampling factor (ratio between LR and HR, page 3 Section 3.1 “s is the downscaling factor”);
executing an upsampling algorithm on the first downsampled image to generate a first reconstructed image having the first resolution (SRNet to produce SR image that is understood to have the same scale/size/dimension/resolution as that of HR image input, in further view of Applicant’s disclosure wherein resolution and scale appear synonymous – e.g. [0119] “having a resolution of 1280x720”);
computing a first reconstruction error based on the first reconstructed image and the first source image (page 5 section 3.4, “One of the main contributions of our work is that we propose a model to learn image downscaling without any supervision signifying that no constraint is applied to the downscaled image. The only objective guiding the generation of the downscaled image is the SR restoration error”, “To do fair comparisons with the EDSR, we only adopt the L1 norm loss as the restoration metric as suggested by [33]”, Equation 8, etc.,; while not required in a basis for rejection in view of Sun as applied, see also Li et al., “Learning a Convolutional Neural Network for Image Compact-Resolution” (cited by Applicant) page 1094 1) Reconstruction Loss); and
updating at least one parameter of the first convolutional neural network based on the first reconstruction error to generate a trained convolutional neural network (page 4 section 3.2 Backward pass “The ResamplerNet is trained using the gradient descent technique and we need to back-propagate gradients from the SRNet through the resampling operation”); wherein
a residual block comprises a portion of the first convolutional neural network that maps the input of the residual block to a residual and then adds the residual to a function of the input of the residual block to generate the output of the residual block (Fig. 1 lower portion illustrating architecture of each light blue ResBlock, wherein the mapped residual is the output of that scale layer prior to that summation with the residual block input following that top skip connection/path); and wherein
each downsampled image has a resolution that is lower than a resolution of a corresponding source image by the first downsampling factor (LR is HR downscaled by factor s, page 3 Section 3.1 “s is the downscaling factor”, page 4 Fig. 2, scale of equation 1, etc.,).
Allowable Subject Matter
Claim(s) 9-20 would be allowable if rewritten or amended (see above regarding Terminal Disclaimer) to overcome the Double Patenting rejections set forth in this Office action.
Dependent claim(s) 2-8 would similarly be allowable if rewritten to overcome (or otherwise overcome – see above re. Terminal Disclaimer) Double Patenting rejections, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims. References of record fail to serve in any obvious combination teaching/ suggesting each and every limitation as required by the instant claims, and reasons for allowance are additionally apparent from the record(s) associated with parent application 17/133,206. See MPEP § 1302.14.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IAN L LEMIEUX whose telephone number is (571)270-5796. The examiner can normally be reached Mon - Fri 9:00 - 6:00 EST.
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/IAN L LEMIEUX/Primary Examiner, Art Unit 2669
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