Sep 19, 2024 · This research evaluates advanced deep learning techniques in medical imaging, specifically Vision Transformers (ViT) and Convolutional Neural Networks (CNNs), ...
This study seeks to identify accurate skin cancer detection applications by comparing the effectiveness of machine learning and deep learning methods. Various ...
In this paper, we evaluate the performance of several state-of-the-art convolutional neural networks in dermoscopic images of skin lesions.
In order to compare the approaches, we look at the generalization capability of the trained model for melanoma identification, cancer detection, and cross- ...
Jan 22, 2024 · A detailed review in this paper explores various algorithms, including machine learning (ML) techniques as well as deep learning (DL) techniques.
In this paper, we evaluate the performance of several state-of-the-art convolutional neural networks in dermoscopic images of skin lesions.
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A technique for automatically identifying skin cancer in dermoscopy pictures is offered, which made use of convolutional functions and depth wise separable ...
Sep 26, 2024 · The model is evaluated through 10-fold cross-validation and the metrics of accuracy, recall, precision, and the F1 score. The results ...
This study provides an overview of various methodologies used in diagnosing skin cancer using image analysis and examines lessons and insights from previous ...
Sep 2, 2024 · This work presents a comparative study of image classification techniques applied to dermatoscopic images for melanoma detection. The chosen ...