BF2SkNet: best deep learning features fusion-assisted framework for multiclass skin lesion classification-Reference-Cited by-同舟云学术

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BF2SkNet: best deep learning features fusion-assisted framework for multiclass skin lesion classification

Published:2022-12-12 Issue: Volume: Page:
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Ajmal Muhammad,Khan Muhammad Attique,Akram Tallha,Alqahtani Abdullah,Alhaisoni Majed,Armghan Ammar,Althubiti Sara A.,Alenezi Fayadh

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-08084-6.pdf

Reference66 articles.

1. Spyridonos P, Gaitanis G, Likas A, Bassukas I (2021) Characterizing malignant melanoma clinically resembling seborrheic keratosis using deep knowledge transfer. Cancers 13:6300

2. Mahbod A, Tschandl P, Langs G, Ecker R, Ellinger I (2020) The effects of skin lesion segmentation on the performance of dermatoscopic image classification. Comput Methods Programs Biomed 197:105725

3. Lakhan MK, Lynch M (2021) Skin pigmentation. Medicine 49:447–452

4. Iqbal I, Younus M, Walayat K, Kakar MU, Ma J (2021) Automated multi-class classification of skin lesions through deep convolutional neural network with dermoscopic images. Comput Med Imaging Graph 88:101843

5. Mahbod A, Schaefer G, Wang C, Dorffner G, Ecker R, Ellinger I (2020) Transfer learning using a multi-scale and multi-network ensemble for skin lesion classification. Comput Methods Programs Biomed 193:105475

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1. LW-XNet for segmentation and classification of skin lesions from dermoscopy images;Expert Systems with Applications;2024-12

2. EAAC-Net: An Efficient Adaptive Attention and Convolution Fusion Network for Skin Lesion Segmentation;Journal of Imaging Informatics in Medicine;2024-08-15

3. TAENet: transencoder-based all-in-one image enhancement with depth awareness;Applied Intelligence;2024-06-08

4. Enhancing Skin Cancer Diagnosis Using Swin Transformer with Hybrid Shifted Window-Based Multi-head Self-attention and SwiGLU-Based MLP;Journal of Imaging Informatics in Medicine;2024-06-05

5. Self-supervised multi-task learning for medical image analysis;Pattern Recognition;2024-06

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