Superpixels-based Segmentation and Classification using Modified Fuzzy C-Means Clustering and Color Features-Reference-Cited by-同舟云学术

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Superpixels-based Segmentation and Classification using Modified Fuzzy C-Means Clustering and Color Features

Published:2024-04-12 Issue: Volume:5 Page:1223-1228
ISSN:
Container-title:2024 10th International Conference on Communication and Signal Processing (ICCSP)
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Author:

Akilandeswari A.¹,Alexander T.Jerry²,Ganesan P³,Janakiraman V.¹,Akila D.⁴,Sajiv G.¹

Affiliation:

1. SIMATS,Saveetha School of Engineering,Chennai,Tamilnadu,India

2. Swarnandhra College of Engineering and Technology,Dept. of ECE,Narsapur,AP,India

3. Vidya Jyothi Institute of Technology,Dept. of Electronics and Communication Engineering,Hyderabad,India

4. SIMTAS,Saveetha College of Liberal Arts and Sciences,Dept of Computer Applications,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10543256/10543221/10543321.pdf?arnumber=10543321

Reference15 articles.

1. autoSMIM: Automatic Superpixel-Based Masked Image Modeling for Skin Lesion Segmentation

2. Multi-Path Minimum Spanning Tree and Superpixel Based Cost Aggregation for Stereo Matching

3. Superpixel Inpainting For Self-Supervised Skin Lesion Segmentation from Dermoscopic Images

4. Possiblistic-Fuzzy C-Means Clustering Approach for the Segmentation of Satellite Images in HSL Color Space

5. A Sample Enhancement Method Based on Simple Linear Iterative Clustering Superpixel Segmentation Applied to Multibeam Seabed Classification

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