PATENT CLAIM ANALYSIS

Application Number: 16353345
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-07
Patent Classification: ["382", "103000"]

Abstract:
Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.

Claim (Index 4):
The method of  claim 3 , wherein receiving the training images further comprises receiving orientations of the sensors relative to one another if the training images are from two or more sensors.

Metadata:
- Claim Count in Document: 13.0
- Percentile: 99.0
- Lexical Diversity: 2.05263
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15253488', '16353361', '13531032', '14503539', '14709536']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3568537078029306
- 35 USC 102 Novelty (BERT): 0.5269155431223567
- Combined Prediction Score: 0.3738598913348732
- Mean Citation Score: 212.577014
- Max Citation Score: 324.15094
- Similarity Product: 209.4809251106072

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test