METHOD AND SYSTEM FOR LEARNING SPECTRAL FEATURES OF HYPERSPECTRAL DATA USING DCNN

Patent №

US 11,615,603

Granted

2023-03-28

Filed 2021

Owner

TATA CONSULTANCY SERVICES LIMITED

Lab

AI components

2

ml · vision

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17201710

The embodiments herein provide a method and system that analyzes the pixel vectors by transforming the pixel vector into two-dimensional spectral shape space and then perform convolution over the image of graph thus formed. Method and system disclosed converts the pixel vector into image and provides a DCNN architecture that is built for processing 2D visual representation of the pixel vectors to learn spectral and classify the pixels. Thus, DCNN learn edges, arcs, arcs segments and the other shape features of the spectrum. Thus, the method disclosed enables converting a spectral signature to a shape, and then this shape is decomposed using hierarchical features learned at different convolution layers of the disclosed DCNN at different levels.

Machine learningVisionG06V 10/143G06V 10/454G06F 18/2413G06F 18/2431G06N 3/045G06N 3/0464G06N 3/0495G06N 3/09+5 more

AI classification

Vision1.00
Machine learning1.00
AI hardware0.27
Speech0.01
Planning0.00
Natural language0.00
Evolutionary computation0.00
Knowledge representation0.00

Ownership

TATA CONSULTANCY SERVICES LIMITED

assignment · 556150345

Assignors

DESHPANDE, SHAILESH SHANKAR, THAKUR, ROHIT, PURUSHOTHAMAN, BALAMURALIDHAR

On an employer assignment, the assignors are typically the inventors.

From the same owner

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