PATENT CLAIM ANALYSIS

Application Number: 15862602
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-02
Patent Classification: ["382", "173000"]

Abstract:
Detecting objects in an image includes: extracting core instance features from the image; calculating feature maps at multiscale resolutions from the core instance features; calculating detection boxes from the core instance features; calculating segmentation masks for each detection box of the detection boxes at the multiscale resolutions of the feature maps; merging the segmentation masks at the multiscale resolutions to generate an instance mask for each object detected in the image; refining the confidence scores of the merged segmentation masks by auxiliary networks calculating pixel level metrics; and outputting the instance masks as the detected objects.

Claim (Index 12):
The method of  claim 9 , wherein the filtering the instance masks in accordance with the density metrics comprises:\n calculating a pixel density discrepancy for every pixel in the image; calculating a differential mask discrepancy for each instance mask; and minimizing the differential mask discrepancy of a collection of surviving masks.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 86.0
- Lexical Diversity: 2.16667
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15296845', '15230229', '15693446', '14801839', '15224487']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3193768108950675
- 35 USC 102 Novelty (BERT): 0.511313926817961
- Combined Prediction Score: 0.3385705224873569
- Mean Citation Score: 226.923176
- Max Citation Score: 242.16208
- Similarity Product: 159.02143289567948

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test