Deep learning in skin lesion analysis for malignant melanoma cancer identification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-16273-1.pdf
Reference22 articles.
1. Adegun A, Viriri S (2020) FCN-based DenseNet framework for automated detection and classification of skin lesions in Dermoscopy images. IEEE Access 8:150377–150396
2. Adegun A, Viriri S (2021) Deep learning techniques for skin lesion analysis and melanoma cancer detection: a survey of state-of-the-art. Artif Intell Rev 54:811s implemented–841
3. Ashraf R et al (2020) Region-of-interest based transfer learning assisted framework for skin Cancer detection. IEEE Access 8:147858–147871
4. Bakkouri I, Afdel K (2019) Computer-aided diagnosis (CAD) system based on multi-layer feature fusion network for skin lesion recognition in dermoscopy images. Multimed Tools Appl 79:20483–20518. https://doi.org/10.1007/s11042-019-07988-1
5. Bakkouri I, Afdel K (2022) MLCA2F: multi-level context attentional feature fusion for COVID-19 lesion segmentation from CT scans. SIViP https://doi.org/10.1007/s11760-022-02325-w
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