Aug 2026· The Arabian journal for science and engineering· Vol 51, pp. 18645 - 18661· 0 citations· 45 references
TL;DR
A hybrid approach that integrates convolutions with linear projections is introduced, combining the ability of convolutions to effectively capture local spatial features with the capacity of linear projections to model global relationships, leading to a more expressive and robust feature representation.
Skin cancer is one of the most common forms of cancer globally, with melanoma being the most fatal form. Early and precise detection is crucial for improving treatment outcomes, as timely disease management dramatically increases survival rates. This study presents a reliable multimodal deep learning framework that int...
Uttam Mittal, S. Varpe, A. Sharma et al.· IEEE Access· 0 citations
Introduction Skin cancer is among the most prevalent malignancies worldwide, and accurate segmentation of skin lesions plays a vital role in its early diagnosis and treatment. Traditional deep learning models face challenges in balancing local feature extraction with global contextual understanding. This study aims to...
Xian-Hong Wang, Muhammad Saeed, Naeem Ahmed et al.· Frontiers in Medicine· 0 citations
The classification of skin lesions from dermoscopic and clinical images remains challenging due to visually similar lesion categories, variability in image acquisition, class imbalance, and limited cross-dataset generalisation, which can undermine the reliability of diagnostic results. Current CNN-based approaches are...
Background/Objectives: Melanoma is a life-threatening skin cancer characterized by aggressive progression and high metastatic potential, making early diagnosis essential for improving patient survival and treatment outcomes. However, accurate automated skin lesion classification remains challenging due to variations in...
Melanoma is a more aggressive type of skin cancer and early detection is critical to good clinical outcomes. Interpretation is difficult, however, due to the fact that dermoscopic images of melanomas and benign lesions can present with similar visual features, such as uneven pigmentation, border variation and texture v...
Ashish Jain, Rashmi Yadav· Natural Resources for Human...· 0 citations
The results demonstrate that deep learning techniques can significantly assist in early detection and classification of skin cancer, thereby supporting dermatologists in clinical decision-making and improving diagnostic efficiency and mortality rates associated with skin cancer.
A. Star, Gibi Linza, Siva Durshika et al.· 0 citations
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