Embedded Skin Lesion Segmentation using Lightweight Encoder-Decoder Architectures-Reference-Cited by-同舟云学术

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Embedded Skin Lesion Segmentation using Lightweight Encoder-Decoder Architectures

Published:2023-02-22 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Artificial Intelligence (ICAI)
language:
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Author:

Ijaz Haris¹,Sultan Hajrah²,Altaf Mishal³,Waris Asim²

Affiliation:

1. School of Electrical Engineering and Computer Science, National University of Science and Technology,Islamabad,Pakistan

2. School of Mechanical and Manufacturing Engineering, National University of Science and Technology(NUST),Islamabad,Pakistan

3. U.S-Pakistan Center For Advance Studies in Energy (USPCASE), National University of Science and Technology(NUST),Islamabad,Pakistan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10136637/10136621/10136688.pdf?arnumber=10136688

Reference27 articles.

1. Skin lesion segmentation using convolutional neural networks with improved U-Net architecture

2. MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentation

3. A Skin Lesion Segmentation Method for Dermoscopic Images Based on Adaptive Thresholding with Normalization of Color Models

4. Learning to Segment Skin Lesions from Noisy Annotations

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1. DTONet a Lightweight Model for Melanoma Segmentation;Bioengineering;2024-04-18

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