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 .
Election/Restrictions
Claims 1-12 and 16 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected group, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 12/29/2025.
35 USC §101 Claim Analysis
Claims 13-15 recites a decoding and segmentation method, “a process”, where the calculation steps, as recited, could not be practicably performed by a human, thus do not fall under an “abstract idea”.
Claim 17 recites a decoding and segmentation device, “a machine”.
Thereby the above-discussed claims are NOT rejected under 35 USC §101.
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 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 of this title, 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.
Claims 13-15 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Karthik (“Semantic segmentation for plant phenotyping using advanced deep learning pipelines” Multimedia Tools and Applications, published Dec 2021) in view of Dixit (“Object Detection and Lane Segmentation Using Multiple Accelerators with DRIVE AGX”, Data Science, June 2019)
As for claim 13, Karthik teaches
A multi-scale feature group decoding method comprising:
[..]
extracting a multi-channel feature from the decoded plane image (Karthik Fig 1 and description: upper left, feature maps shown in blocks 1-3 have 3, 16 and 16 channels respectively, i.e. “multi channel features”; from Fig 1 description: “Each blue box represents a multi-channel feature map and the number of channels are represented on top of them.”); and
reconstructing the multi-scale feature group from the multi-channel feature (Fig 1, right-side path, reading from bottom-up:upscaling feature maps from 16x16 to 32x32 etc to 256x256; the entire set of intermediate upscaled feature maps from 16x16 to 256x256 can be called a “multi-scale feature group”)
Karthik does not specifically teach, Dixit however teaches
decoding a plane image; (Dixit pg 5 top Figure, performing JPEG decoding prior to the primary segmentation workflow)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Karthik by including features of Dixit, as they both pertain to the art of image segmentation. One of ordinary skill in the art at the time of the invention would have been motivated to combine said teachings, in order to segment an image that was previously encoded, as taught by Dixit.
As for independent claim 17, please see discussion of analogous claim 13 above.
As for claim 14, the combination of Karthik and Dixit teaches
wherein reconstructing the multi- scale feature group comprising:
dividing the multi-channel feature into a plurality of features (Karthik Fig 1 upper left: deriving 16-channel feature map from a 3-channel feature map); and
reconstructing each of the divided feature to an original resolution, (Karthik Fig 1 upper right: reconstructing the original 256x256 resolution)
wherein reconstruction to the original resolution is performed based on at least one of upscaling, downscaling, a convolution layer, a fully-connected layer or an activation function. (Karthik Fig 1 entire right branch performs incremental upscaling)
As for claim 15, the combination of Karthik and Dixit teaches
a feature in the multi-scale feature group is reconstructed by fusing a pre-reconstructed (NOTE: “pre-reconstructed” does not indicate any specific result, it only calls for some kind of step prior to reconstruction; for example the cropping operations indicated by long grey arrows in the center of the image can be called “pre-reconstruction” of the corresponding feature map – Karthik ch 2.2.1 par 2 “The feature map of the contracting path is cropped before mapping..”) lower level feature or a pre-reconstructed higher level feature with the feature reconstructed to the original resolution (Karthik Fig 1 upper right, the 256x256 feature map upscaled through the upscaling branch is of the original resolution, which is fused with a cropped 16-channel feature map input from the top left to produce a 16-channel 256x256 feature map – Karthik ch 2.2.1 par 2 “there is a concatenation with the feature map of the contracting path which corresponds to that particular convolution..” ; furthermore, the 16-channel cropped feature map could be called “lower-level” relative to the 32-channel feature map it is being fused with)
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW M MOYER whose telephone number is (571)272-9523. The examiner can normally be reached on Monday-Friday 9-5 EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Moyer can be reached on (571)272-9523. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MARK ROZ/
Primary Examiner, Art Unit 2669