DETAILED ACTION
[1] Remarks
I. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
II. Claims 1-16 are pending and have been examined, where claims 1-4 and 15-16 is/are rejected, claim 5-14 is/are objected to. Explanations will be provided below.
III. Inventor and/or assignee search were performed and determined no double patenting rejection(s) is/are necessary.
IV. Patent eligibility (updated in 2019) shown by the following: Claims 1-16 pass patent eligibility test because there is/are no limitation or a combination of limitations amounting to an abstract idea
Also, the following limitation or the combinations of the limitations: “identifying one or more anchor points within the ground-truth instance box, each anchor point having an associated image space location; calculating, for each anchor point, a loss indicative of a difference between a box predicted by the anchor point and the ground-truth instance box; and weighting the loss for each anchor point based on the distance of the anchor point from a boundary of the ground-truth instance box” effects a transformation or a reduction of a particular article to a different state or thing / adds a specific limitation(s) other than what is well-understood, routine and conventional in the field, or adding unconventional steps that confine the claim to a particular useful application and providing improvements to the technical field of deep learning, which recite additional elements that integrate the judicial exception into a practical application and amounting significant more.
V. The PCT application, PCT/US2022/013485, is considered and the examiner determined no reference prior art are relevant to the claims of the current application.
[2] Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Use of the word “means” (or “step for”) in a claim with functional language creates a rebuttable presumption that the claim element is to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is invoked is rebutted when the function is recited with sufficient structure, material, or acts within the claim itself to entirely perform the recited function. Absence of the word “means” (or “step for”) in a claim creates a rebuttable presumption that the claim element is not to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is not invoked is rebutted when the claim element recites function but fails to recite sufficiently definite structure, material or acts to perform that function.
Claim elements in this application that use the word “means” (or “step for”) are presumed to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Similarly, claim elements that do not use the word “means” (or “step for”) are presumed not to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
Claim(s) 1-16 are not interpreted under 35 U.S.C. 112(f) or pre-AIA U.S.C. 112 6th paragraph because of the following reason(s): limitations are modified by sufficient structure or material for performing the claimed function; they are method claims with no association to generic placeholder(s); they are CRM claims.
Upon examination of the specification and claims, the examiner has determined, under the best understanding of the scope of the claim(s), rejection(s) under 35 U.S.C. 112(a)/(b) is/is not necessitated because of the following reasons: sufficient support are provided in the written description / drawings of the invention.
[3] Grounds of 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) person shall be entitled to a patent unless—
(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; or
(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.
or
(b) the invention was patented or described in a printed publication in this or a foreign country or in public use or on sale in this country, more than one year prior to the date of application for patent in the United States.
Claims 1-4 and 15-16 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Hu (US 20220036548).
Regarding claim 1, Hu discloses a method for training an object detector, the object detector comprising:
a backbone (see figure 2, 215 is read as the backbone);
a feature pyramid coupled to the backbone (see figure 2, 210 is read as the ); and
a detection head coupled to each level of the feature pyramid, each detection head having a classification subnet and a localization subnet (see figure 2, the subnets are detection heads having classification and localization);
the method comprising:
defining, on a level of the feature pyramid, a ground-truth instance box enclosing an object of interest in a class for which the object detector is being trained (see paragraph 74, second subnetwork 225 is a regression subnet that is attached to each feature map of the feature pyramid network 210 and is in parallel to the first subnetwork 220, where the design of the second subnetwork 225 is identical to that of the first subnetwork 220, except that the last convolutional layer has 4A filters, therefore, the shape of the output feature map would be (W,H,4A) where W and H are proportional to the width and height of the input feature map, … where the second subnetwork 225 outputs 4 numbers for each anchor box that predict the relative offset, in terms of center coordinates, width and height, between the anchor box and the ground truth box);
identifying one or more anchor points within the ground-truth instance box, each anchor point having an associated image space location (see end of paragraph 74 below, the refinement of the anchors is read as the identification of the anchor points);
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calculating, for each anchor point, a loss indicative of a difference between a box predicted by the anchor point and the ground-truth instance box (see paragraph 75, a comparison is made between the predictions for the 4 coordinates of the bounding boxes and the coordinates of the bounding boxes for the ground truths, the loss of RetinaNet is a multi-task loss that contains two terms: one for localization, denoted as Lloc); and
weighting the loss for each anchor point based on the distance of the anchor point from a boundary of the ground-truth instance box (paragraph 75, localization loss (Lloc) and the classification loss (Las) are calculated based on the comparison made between the predictions for the 4 coordinates of the bounding boxes and the coordinates of the bounding boxes for the ground truths, where the localization loss Lloc is a regression loss, where this regression loss is read as the distance between the anchor point from a boundary of the ground-truth instance box).
Regarding claim 2, Hu discloses the method of claim 1 wherein:
the classification subnet predicts a probability of an object of interest at a location for each anchor point (see paragraph 69, showing the binary cross entropy function); and
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the localization subnet predicts a distance from each anchor point to boundaries of the ground-truth instance box (paragraph 75, localization loss (Lloc) and the classification loss (Las) are calculated based on the comparison made between the predictions for the 4 coordinates of the bounding boxes and the coordinates of the bounding boxes for the ground truths, where the localization loss Lloc is a regression loss, where this regression loss is read as the distance between the anchor point from a boundary of the ground-truth instance box).
Regarding claim 3, Hu discloses the method of claim 1 wherein losses associated with the anchor points having image space locations closer to a boundary of the ground-truth instance box are down-weighted (see paragraph 81, the focal loss down-weights bounding boxes predicted during training for non-CL morphology or background within the plurality of training sets of images and focuses training on bounding boxes predicted for the CL).
Regarding claim 4, Hu discloses the method of claim 3 wherein the closer an image space location of an anchor point to the boundary of the ground-truth instance box, the greater the down-weighting of the loss associated with the anchor point (see paragraph 70, As pt1, the modulating factor (1−pt) goes to 0 and the loss for well-classified examples is down-weighted. The focusing parameter γ smoothly adjusts the rate at which easy examples are down-weighted, where adjusting the adjusting the rate adjusting the down-weighting greater and lower).
Regarding claims 15-16, see paragraph 25 of Hu which discloses at least one processor to perform the limitations of claim 1.
[4] Claim Objections
Claim(s) 5-12 is/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.
Regarding claim 5, Hu discloses the method of claim 3 wherein weights are applied only to positive anchor points, wherein positive anchor points have an image space location within a
Hu teaches away the method of claim 3 wherein weights are applied only to positive anchor points, wherein positive anchor points have an image space location within a shrunken version of the ground-truth instance box, thereby suggesting that a person of ordinary skill in the art would not have been motivated to combine prior art elements to arrive at the claimed invention of claims 1, 3 and 5.
COHEN (US 20180322339) discloses the method of claim 3 wherein weights are applied only to positive anchor points, wherein positive anchor points have an image space location within a shrunken version of the ground-truth instance box (see paragraph 91, training data 122(b) may be generated by vertically shrinking a bounding box that contains a single paragraph so that it is missing some lines, training data 122(b) may also be generated by shrinking the bounding box horizontally so that parts of the paragraph fall out of the bounding box).
However, Hu discloses
Claim(s) 6-14 is/are objected as well because it is dependent on a claim with allowable subject matter.
CONTACT INFORMATION
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEX LIEW (duty station is located in New York City) whose telephone number is (571)272-8623 (FAX 571-273-8623), cell (917)763-1192 or email alexa.liew@uspto.gov. Please note the examiner cannot reply through email unless an internet communication authorization is provided by the applicant. The examiner can be reached anytime.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, MISTRY ONEAL R, can be reached on (313)446-4912. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALEX KOK S LIEW/Primary Examiner, Art Unit 2674 Telephone: 571-272-8623
Date: 7/4/25
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