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 5):
The method of  claim 1 , wherein receiving the training images comprises receiving the training images from one or more sensors and parameters related to at least one of one or more positions of the one or more sensors, orientation of illumination source that associates formation of the training images, time, date, latitude, or longitude.

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): 0.3571266654790507
- 35 USC 102 Novelty (BERT): 0.5219517951654629
- Combined Prediction Score: 0.3736091784476919
- Mean Citation Score: 212.577014
- Max Citation Score: 324.15094
- Similarity Product: 252.94820084150075

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