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
RESPONSE TO ARGUMENTS
35 USC 102 Rejection
After carefully reviewing applicant amendments, prior art guidance and claim limitations, claim limitations are sufficient to overcome grounds of rejection.
35 USC 103 Rejection
Applicant submits claimed “feature pyramid network” is not equivalent to applied reference Manautou’s feature pyramid network. Applicant also submits Substituting Wang's computationally intensive multi-branch architecture (with pyramid pooling, dual attention, deconvolutions, and conditional random fields for dense, subpixel-level semantic segmentation (see, Wang at paras. [0005]-[0014])) would fundamentally alter its principle of operation by shifting to exhaustive pixel-wise scene parsing.
In response, examiner submits “Feature Pyramid Network” is broad under broadest reasonable interpretation. In response to applicant's argument that the references fail to show certain features of applicant’s invention, it is noted that the features upon which applicant relies (i.e., Feature Pyramid Network specifics (e.g. top-down pathway, lateral connections, multi-level outputs, etc.) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Examiner submits under broadest reasonable interpretation, “Feature Pyramid Network” can be read on by any classifier architecture that forms and uses a pyramid/multi-scale hierarchy of feature representations. Wang builds multi-scale pooled features (P1/P2/P3) from feature maps and concatenates them into a “pyramid pooling feature map”. A “feature pyramid network”, under BRI, it is interpreted as a network that constructs pyramid/multi-scale features used downstream for classification [0052].
Applicant submits Wang is disqualified because it is segmentation. In response, examiner submits claim limitations only require classifying pollen in the captured image using a classifier defining a feature pyramid network. A segmentation network classifies pixels/regions (and therefore the pollen depicted) into classes; this still satisfies “classifying pollen including in the captured image into one of multiple classes” under BRI.
As to applicant “principle of operation” 103 incompatibility argument, examiner submits 103 incompatibility in “principle of operation” are not sufficient to overcome for the following reasons: (1) Neither reference directly teaches away from the combination (2) claims do not recite the constraints being relied upon that applicant submits would be destroyed via reference combination.
In view of above arguments examiner submit 103 rejection is sufficient and respectfully maintained.
ALLOWABLE SUBJECT MATTER
Claims 21-24 are allowed.
The following is an examiner’s statement of reasons for allowance: Regarding independent claim 21, the prior art of record fails to teach or fairly suggest the combination of all limitations of independent claim 21 that includes:
Claim 21:
…
“
a platform configured to support pollen in the pollen imaging apparatus; an enclosure configured to cooperate with the platform to inhibit ambient light from the pollen disposed on the platform; an image capture device configured to capture the image of the pollen disposed on the platform of the pollen imaging apparatus; a light fixture configured to illuminate the pollen on the platform of the pollen imaging apparatus, when the image capture device captures the image of the pollen; and a network interface configured to receive instructions for capturing the image and/or configured to transmit the captured image to at least one computing device.
”
Regarding dependent claims 22-24 these claims are allowed because of their dependence on independent claim 21 which has been deemed allowable subject matter above.
CLAIM REJECTIONS - 35 USC § 103
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over
Manautou et al. (U.S. Publication 2019/0293539) in view of Wang (U.S. Publication 2021/0406582)
As to claims 1, 7 & 11, Manautou discloses a computer-implemented method for use in determining viability of pollen, through image processing, the method comprising: capturing, by a pollen imaging apparatus, an image of pollen disposed on a platform of the pollen imaging apparatus ([0521-0533] discloses “particle collection surface”, Pollen grains S005 may be on the surface of a side 5010 and illuminated S011A-B by a light sources); classifying, by a computing device, coupled to the pollen imaging apparatus, pollen included in the captured image into one of multiple classes, based on a classifier; ([0148, 0553, 0561] discloses Image recognition engine receives the image of the collected particles taken by the optical subsystem and analyzes the image using particles-discrimination algorithm parameters it previously received frame the cloud. For example, particles discrimination algorithms running in the particle identification subsystem may identify the collected particle as grass pollen. Some examples of parameters that may be considered in a particle-discrimination algorithm included autofluorescence properties (e.g., Intensity of autofluorescence), size, shape, length of polar axes, length of equatorial axes (or diameter), ratio of polar axis to equatorial axis (P/E ratio), number of apertures, type of apertures, shape of apertures, position of apertures, lack of apertures, color characteristics, geometrical features, type of symmetry (2.9., radial symmetry or bilateral symmetry}, lack of symmetry, other parameters, weights, or combinations of these. One or more of these parameters may be derived or extracted frame optical system measurements, specified as a threshold, and then used as a discrimination algorithm parameter to discriminate particles”; “light-based methodology includes five different measurement techniques including deep neural network machine learning and advanced algorithms toe extract unique particle signatures leading to classification. A media cartridge is provided that captures particles for physical record archiving, future studies, advanced studies in a laboratory, and combinations of these. An analysis may include particle feature extraction, vector extraction, executing a classifier algorithm, particle classifications, and aggregating the information into a results file, or combinations of these”);
determining, by the computing device, one or more metrics associated with the one or more classes of pollen included in the image; and providing, by the computing device, to a user, an indication of viability of the pollen based on whether the one or more metrics satisfy a defined threshold, thereby instructing the user in the viability of the pollen included in the image.
([0148, 0558-0561] discloses "The system can provide counts, trends, and predictive data and analytics displayed via a web application or mobile application. The application allows for customizing alerts for efficient vineyard management operation’; "results file may be transmitted to a user's mobile device for display. Particle detection techniques may include morphology (e.g., shape and size), UV fluorescence (e.9., NADH & NAD excitation), colorimetry (e.g., color parameters}, topography (e.g., height and texture), Internal structure, or combinations of these"))
Manautou is silent to classifier defining a feature pyramid network.
However, Wang’s [0071] discloses classifier defining a feature pyramid network.
It would have been obvious to one of ordinary skill in the art at the time of effective filing to modify Manautou’s disclosure to include the above limitations in order to provide an airbourne particle collection system capable of improved and more accurate image analysis and classification.
As to claim 2, Manautou in view of Wang discloses everything as disclosed in claim 1. In addition, Manautou discloses wherein the pollen imaging apparatus includes an enclosure, which cooperates with the platform to inhibit ambient light from the pollen ([0527]); and wherein the method further comprises lighting, by a light fixture, the pollen when capturing the image of the pollen. ([0533-0536])
As to claims 3, 8 & 12, Manautou in view of Wang discloses everything as disclosed in claims 1, 7 & 11 respectively. In addition, Manautou discloses wherein the classifier defines a neural network, and wherein the neural network includes a network ([0146], [0559]). Wang discloses further teaches RetinaNet architecture including the feature pyramid network and a residual convolutional ([0171-0175])
As to claims 4, 9 & 13, Manautou in view of Wang discloses everything as disclosed in claims 1, 7 & 11 respectively. In addition, Manautou discloses wherein the one or more classes of pollen includes a good class and a bad class; and wherein the one or more metrics includes a percentage of the pollen included in the at least one image classified in one of the good class and the bad class. ([0199, 0416-0419, 0558-0561])
As to claims 5, 10 & 14, Manautou in view of Wang discloses everything as disclosed in claims 7 & 11 respectively. In addition, Manautou discloses wherein the executable instructions, when executed by the at least one processor to provide the indication of viability, cause the at least one processor to display a pass or fail indicator to the user, at a presentation unit of a portable communication device including the at least one processor, based on whether the one or more metrics satisfies the defined threshold. ([0148, 0558-0561] discloses "The system can provide counts, trends, and predictive data and analytics displayed via a web application or mobile application. The application allows for customizing alerts for efficient vineyard management operation’; "results file may be transmitted to a user's mobile device for display. Particle detection techniques may include morphology (e.g., shape and size), UV fluorescence (e.9., NADH & NAD excitation), colorimetry (e.g., color parameters}, topography (e.g., height and texture), Internal structure, or combinations of these"))([0199, 0416-0149, 0558-0561))
As to claims 6 & 20, Manautou in view of Wang discloses everything as disclosed in claims 1 & 11 respectively. In addition, Manautou discloses wherein the computing device includes a portable computing device associated with the user; and/or wherein the platform defines an acrylic, black surface. ([0085, 0133-0135])
As to claim 15, Manautou in view of Wang discloses everything as disclosed in claim 11. In addition, Manautou discloses wherein the at least one computing device includes a portable computing device associated with the user. (See Fig. 1)
As to claim 16, Manautou in view of Wang discloses everything as disclosed in claim 11. In addition, Manautou discloses the pollen imaging apparatus; wherein the pollen imaging apparatus is configured to: capture the image of the pollen disposed on the platform of the pollen imaging apparatus ([0521-0533] discloses “particle collection surface”, Pollen grains S005 may be on the surface of a side 5010 and illuminated S011A-B by a light sources); and transmit the image to the at least one computing device. ([0148, 0558-0561] discloses "The system can provide counts, trends, and predictive data and analytics displayed via a web application or mobile application. The application allows for customizing alerts for efficient vineyard management operation’; "results file may be transmitted to a user's mobile device for display. Particle detection techniques may include morphology (e.g., shape and size), UV fluorescence (e.9., NADH & NAD excitation), colorimetry (e.g., color parameters}, topography (e.g., height and texture), Internal structure, or combinations of these"))
As to claim 17, Manautou in view of Wang discloses everything as disclosed in claim 16. In addition, Manautou discloses wherein the pollen imaging apparatus further includes the platform and an enclosure, which cooperates with the platform to inhibit ambient light from the pollen disposed on the platform. ([0533-0536])
As to claim 18, Manautou in view of Wang discloses everything as disclosed in claim 16. In addition, Manautou discloses wherein the pollen imaging apparatus further includes an image capture device configured to capture the image of the pollen disposed on the platform of the pollen imaging apparatus. ([0533-0536])
As to claim 19, Manautou in view of Wang discloses everything as disclosed in claim 16. In addition, Manautou discloses wherein the pollen imaging apparatus further includes a light fixture configured to illuminate the pollen on the platform of the pollen imaging apparatus, when the image capture device captures the image of the pollen. ([0533-0536])
CONCLUSION
No prior art has been found for claims 21-24 in their current form.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Stephen P Coleman whose telephone number is (571)270-5931. The examiner can normally be reached Monday-Thursday 8AM-5PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Moyer can be reached at (571) 272-9523. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Stephen P. Coleman
Primary Examiner
Art Unit 2675
/STEPHEN P COLEMAN/ Primary Examiner, Art Unit 2675