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 .
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 §§ 706.02(l)(1) - 706.02(l)(3) 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).
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Claim 1-4, 6-12, and 14-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-20 of U.S. Patent No. 12148131 B2. Although the claims at issue are not identical, they are not patentably distinct from each other.
Regarding claims 1, 9, and 17. A system comprising:
at least one processor; and at least one memory including programming instructions that, upon execution by the at least one processor, cause the at least one processor to:
receive an image including a masked region, wherein the image is divided into patches comprising a masked patch that includes at least a portion of the masked region (see claim 1 of U.S. Patent No. 12148131 B2, receive an image including a masked region and an unmasked region; divide the received image into a plurality of patches including a masked patch, wherein the masked patch includes at least a portion of the masked region of the image);
generate a predicted token for the masked patch using an unquantized feature vector encoded from the masked patch region (see claim 1 of U.S. Patent No. 12148131 B2, generate a predicted token for the masked patch using a feature vector encoded from the masked patch, wherein the feature vector is unquantized;);
determine a quantized vector of the masked patch using at least the predicted token of the masked patch (see claim 1 of U.S. Patent No. 12148131 B2, determine a quantized vector of the masked patch using at least the generated predicted token); and
generate an output image based on quantized vectors that include the quantized vector of the masked patch, the output image including inpainting corresponding to the masked region (see claim 1 of U.S. Patent No. 12148131 B2, generate an output image from the set of quantized vectors, whereby the output image includes the unmasked region of the received image and image inpainting in a region corresponding to the masked region in the received image).
Regarding claims 2, 10, and 18. The system of claim 1, wherein the programming instructions further cause the processor to:
determine a token for an unmasked patch in the patches corresponding to the image, the unmasked patch consisting of portion(s) of the image outside the masked region (see claim 2 of U.S. Patent No. 12148131 B2, determine a token for the unmasked patch using an unmasked patch-specific codebook; wherein the unmasked patch includes no portion of the masked region of the image); and
determine a quantized vector for the unmasked patch, wherein the quantized vector for the unmasked patch is included in the quantized vectors used to generate the output image (see claim 2 of U.S. Patent No. 12148131 B2, determine a quantized vector of the unmasked patch using the unmasked patch- specific codebook and the determined token for the unmasked patch; include the determined quantized vector of the unmasked patch into the set of quantized vectors associated with the plurality of patches).
Regarding claims 3, 11, and 19. The system of claim 2,
wherein the token for the unmasked patch is mapped to the quantized vector for the unmasked patch based on an unmasked patch-specific codebook (see claim 3 of U.S. Patent No. 12148131 B2, wherein the masked patch-specific codebook includes a map of token values to quantized latent vectors that is generated using machine learning with masked patch data used as training data), and
wherein the predicted token for the masked patch is mapped to the quantized vector for the masked patch based on a masked patch -specific codebook that is independent from the unmasked patch-specific codebook (see claim 3 of U.S. Patent No. 12148131 B2, wherein the unmasked patch-specific codebook includes a map of token values to quantized latent vectors that is generated using machine learning with unmasked patch data used as training data).
Regarding claims 4 and 12. The system of claim 3, wherein the masked patch-specific codebook and the unmasked patch-specific codebook are generated by different machine learning models (see claim 4 and 10 of U.S. Patent No. 12148131 B2).
Regarding claims 6, 14, and 20. The system of claim 3, wherein the masked patch-specific codebook is generated by a machine learning model trained using masked patch-specific training data, and wherein the unmasked patch-specific codebook is generated by a machine learning model trained using unmasked patch-specific training data that is independent from the unmasked patch-specific codebook (see claim 17 and 10 of U.S. Patent No. 12148131 B2).
Claim 5 and 13 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 12141995 B2 in view of U.S. Patent No. 12333715 B2.
Regarding claims 5 and 13. U.S. Patent No. 12141995 B does not expressly teach the system of claim 4, wherein the machine learning models are trained based on independent training data sets.
The U.S. Patent No. 12141995 B2 teaches that Even though these images are independent of the training dataset used to create the model, the validation dataset still has a small positive bias in accuracy because it is used to monitor and optimize the progress of the model training (see Col. 20, lines 59-63).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the U.S. Patent No. 12141995 B2 by the U.S. Patent No. 12141995 B2 to obtain these images are independent of the training dataset used to create the model, the validation dataset still has a small positive bias in accuracy because it is used to monitor and optimize the progress of the model training, in order to provide wherein the machine learning models are trained based on independent training data sets. Therefore, combining the elements from prior arts according to known methods and technique would yield predictable results.
Allowable Subject Matter
Claims 7-8 and 15-16 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/XIN JIA/Primary Examiner, Art Unit 2663
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