LAN, Kun, GAO, Feiyang, JIANG, Xiaoliang, CHENG, Jianzhen und FONG, Simon, 2025. Enhanced Cutaneous Melanoma Segmentation in Dermoscopic Images Using a Dual U-Net Framework with Multi-Path Convolution Block Attention Module and SE-Res-Conv. Computers, Materials & Continua. 1 September 2025. Vol. 84, no. 3, p. 4805-4824. DOI 10.32604/cmc.2025.065864.
Elsevier - Harvard (with titles)Lan, K., Gao, F., Jiang, X., Cheng, J., Fong, S., 2025. Enhanced Cutaneous Melanoma Segmentation in Dermoscopic Images Using a Dual U-Net Framework with Multi-Path Convolution Block Attention Module and SE-Res-Conv. Computers, Materials & Continua 84, 4805-4824. https://doi.org/10.32604/cmc.2025.065864
American Psychological Association 7th editionLan, K., Gao, F., Jiang, X., Cheng, J., & Fong, S. (2025). Enhanced Cutaneous Melanoma Segmentation in Dermoscopic Images Using a Dual U-Net Framework with Multi-Path Convolution Block Attention Module and SE-Res-Conv. Computers, Materials & Continua, 84(3), 4805-4824. https://doi.org/10.32604/cmc.2025.065864
Springer - Basic (author-date)Lan K, Gao F, Jiang X, Cheng J, Fong S (2025) Enhanced Cutaneous Melanoma Segmentation in Dermoscopic Images Using a Dual U-Net Framework with Multi-Path Convolution Block Attention Module and SE-Res-Conv.. Computers, Materials & Continua 84:4805-4824. https://doi.org/10.32604/cmc.2025.065864
Juristische Zitierweise (Stüber) (Deutsch)Lan, Kun/ Gao, Feiyang/ Jiang, Xiaoliang/ Cheng, Jianzhen/ Fong, Simon, Enhanced Cutaneous Melanoma Segmentation in Dermoscopic Images Using a Dual U-Net Framework with Multi-Path Convolution Block Attention Module and SE-Res-Conv., Computers, Materials & Continua 2025, 4805-4824.