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An optimized boosting framework for skin lesion segmentation and classification
Skin Lesion (SL) prediction and segmentation is the trending topic in the medical imaging industry for finding different disease severity. But the...
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A three-tier BERT based transformer framework for detecting and classifying skin cancer with HSCGS algorithm
Skin cancer is the process of identifying and diagnosing, a disease in which abnormal skin cells grow and spread uncontrollably. An innovative deep...
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Advancements in skin cancer classification: a review of machine learning techniques in clinical image analysis
Early detection of skin cancer from skin lesion images using visual inspection can be challenging. In recent years, research in applying deep...
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Feature selection and pattern recognition for different types of skin disease in human body using the rough set method
Disease analysis is one of the applications of data mining. The rough set is knowledge and information based method to help human decision-making,...
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An Optimized MSER Using Bat Algorithm for Skin Lesion Detection
Detecting regions of interest in skin lesion images is of great significance in dermatological image analysis. In this article, we present a novel...
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Comparison of CNNs and ViTs for the Detection of Human Skin Lesions
This study aims to evaluate the effectiveness of eight deep-learning models in skin lesion detection using dermatoscopic images. For this purpose,...
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Survey on Computational Techniques for Pigmented Skin Lesion Segmentation
AbstractSkin lesion segmentation is the first step in skin lesion assessment, and it can help with the following classification task. It is a complex...
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SKINC-NET: an efficient Lightweight Deep Learning Model for Multiclass skin lesion classification in dermoscopic images
Diagnosing skin cancer through visual image examinations is time-consuming and error-prone, as the similar appearance and variations within each type...
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Interactive Attention Sampling Network for Clinical Skin Disease Image Classification
Skin disease is one of the global burdens of disease, and affects around 30% to 70% individuals worldwide. Effective automatic diagnosis is...
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Deep Learning Model with Atrous Convolutions for Improving Skin Cancer Classification
Skin cancer is the most common problem all over the world, and some forms of skin cancer are not as aggressive as melanoma. It is vital to identify...
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A comprehensive survey on emotion recognition based on electroencephalograph (EEG) signals
Emotion recognition using electroencephalography (EEG) is becoming an interesting topic among researchers. It has made a remarkable entry in the...
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DOTHE based image enhancement and segmentation using U-Net for effective prediction of human skin cancer
Skin cancer is a disorder that is becoming more prevalent around the world and is responsible for numerous mortality. Skin cancer starts in one organ...
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LSNet: a deep learning based method for skin lesion classification using limited samples and transfer learning
When analyzing skin lesion image data using deep learning, the lack of a sufficient amount of effective training data poses a challenge. Although...
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AutYOLO-ATT: an attention-based YOLOv8 algorithm for early autism diagnosis through facial expression recognition
Autism Spectrum Disorder (ASD) is a developmental condition resulting from abnormalities in brain structure and function, which can manifest as...
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Enhancing Monkeypox Detection: A Machine Learning Approach to Symptom Analysis and Disease Prediction
Monkeypox disease, caused by the monkeypox virus, is a highly communicable disease and has prompted the World Health Organization to declare it as a...
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Machine learning for human emotion recognition: a comprehensive review
Emotion is an interdisciplinary research field investigated by many research areas such as psychology, philosophy, computing, and others. Emotions...
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An Improved VGG Model for Skin Cancer Detection
Skin cancer is one of the most prevalent malignancies in humans and is generally diagnosed through visual means. Since it is essential to detect this...
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An effective multiclass skin cancer classification approach based on deep convolutional neural network
Skin cancer is one of the most dangerous types of cancer due to its immediate appearance and the possibility of rapid spread. It arises from...
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Comparative study and analysis on skin cancer detection using machine learning and deep learning algorithms
Exposure to UV rays due to global warming can lead to sunburn and skin damage, ultimately resulting in skin cancer. Early prediction of this type of...
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EdgeMixup: Embarrassingly Simple Data Alteration to Improve Lyme Disease Lesion Segmentation and Diagnosis Fairness
Lyme disease is a severe skin disease caused by tick bites, which affects hundreds of thousands of people. One task in diagnosing Lyme disease is...