PATENT CLAIM ANALYSIS

Application Number: 15752430
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-01
Patent Classification: ["382", "156000"]

Abstract:
A method and apparatus for processing an image of fragmented material to identify fragmented material portions within the image is disclosed. The method involves receiving pixel data associated with an input plurality of pixels representing the image of the fragmented material. The method also involves processing the pixel data using a convolutional neural network, the convolutional neural network having a plurality of layers and producing a pixel classification output indicating whether pixels in the input plurality of pixels are located at one of an edge of a fragmented material portion, inwardly from the edge, and at interstices between fragmented material portions. The convolutional neural network includes at least one convolution layer configured to produce a convolution of the input plurality of pixels, the convolutional neural network having been previously trained using a plurality of training images including previously identified fragmented material portions. The method further involves processing the pixel classification output to associate identified edges with fragmented material portions.

Claim (Index 14):
The method of  claim 1  wherein processing the pixel data using the convolutional neural network further comprises processing the pixel classification output in a further neural network layer to generate a size distribution output, the neural network having been previously trained using a plurality of fragmented material training images including fragment size indications for the fragmented material portions.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 88.0
- Lexical Diversity: 2.3662
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15571463', '15224289', '15524944', '15690037', '14609775']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3978612235603979
- 35 USC 102 Novelty (BERT): 0.5170590000734239
- Combined Prediction Score: 0.4097810012117005
- Mean Citation Score: 278.521406
- Max Citation Score: 320.0317
- Similarity Product: 248.89039117720128

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

Dataset: test