A study of accuracy variation from shallow to deep learning methods for the classification of ships using SAR satellite images

Shovakar Bhattacharjee; Shovakar Bhattacharjee; Palaniswami Shanmugam; Sukhendu Das

doi:10.1364/HMISE.2023.HW5C.5

Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES)
Technical Digest Series (Optica Publishing Group, 2023),
paper HW5C.5
•https://doi.org/10.1364/HMISE.2023.HW5C.5

A study of accuracy variation from shallow to deep learning methods for the classification of ships using SAR satellite images

Shovakar Bhattacharjee, Palaniswami Shanmugam, and Sukhendu Das

Hyperspectral/Multispectral Imaging and Sounding of the Environment 2023

Munich Germany
30 July–3 August 2023
ISBN: 978-1-957171-24-1

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Image Processing, Algorithm Development, and Machine Learning (HW5C)

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S. Bhattacharjee, P. Shanmugam, and S. Das, "A study of accuracy variation from shallow to deep learning methods for the classification of ships using SAR satellite images," in Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES), Technical Digest Series (Optica Publishing Group, 2023), paper HW5C.5.

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Abstract

Accuracy in image classification with deep learning varies with CNN layer depth. A study has been conducted for ship classification in SAR satellite images to understand the accuracy variation from shallow to deep model depth.

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