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Melanoma Detection Using Convolutional Neural Networks
The prevalence of skin cancer is a huge social issue. Melanoma is one type of skin cancer which is known as malignant melanoma. It is the most...
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Melanoma Classification Using Deep Learning
The prevalence of skin cancer, specifically melanoma, constitutes a significant global health concern, thus giving rise to intricate detection...
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Identify Melanoma Using CNN
Skin cancer is a common disease that affects mankind significantly every year there are more new cases of skin cancer than the combined incidence of...
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Automated Detection of Melanoma Skin Disease Using Classification Algorithm
The advancement of modern technology has enabled the diagnosis of various skin diseases through image processing. Researchers face significant...
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Ensemble learning with weighted voting classifier for melanoma diagnosis
Melanoma, the most lethal type of skin cancer, presents a substantial public health challenge. Detecting melanoma promptly is paramount for enhancing...
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Enhancing Melanoma Skin Cancer Detection with Machine Learning and Image Processing Techniques
Detecting early stage melanoma skin cancer is a challenging and critical task in the fields of medical imaging and computer vision. In recent years,...
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Transfer learning-based quantized deep learning models for nail melanoma classification
Skin cancer, particularly melanoma, has remained a severe issue for many years due to its increasing incidences. The rising mortality rate associated...
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Impact of optimizers functions on detection of Melanoma using transfer learning architectures
Early diagnosis-treatment of melanoma is very important because of its dangerous nature and rapid spread. When diagnosed correctly and early, the...
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Deep learning in skin lesion analysis for malignant melanoma cancer identification
The higher rate of skin diseases caused by infections, allergies, lifestyle changes, increased use of chemicals, unhealthy food habits, and...
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Automatic Detection of Melanoma in Human Skin Lesions
This work proposes a methodology for the automatic detection of melanoma skin cancer. Worldwide, this type of cancer has become a public health...
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Skin lesion analysis towards melanoma detection using optimized deep learning network
The deadliest form of skin lesion is known as melanoma. Detection of melanoma at earlier stages significantly raises the rate of survival....
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Melanoma skin cancer detection using deep learning-based lesion segmentation
Extreme caution should be exercised while dealing with any form of skin cancer, but especially malignant melanoma. It’s also on the rise, especially...
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Multi-level Graph Representations of Melanoma Whole Slide Images for Identifying Immune Subgroups
Stratifying melanoma patients into immune subgroups is important for understanding patient outcomes and treatment options. Current weakly supervised...
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IVE-MDNet: Intensity Value Estimation Model Combined with a Transfer Learning Approach for Melanoma Skin Cancer Diagnosis
The percentage of people affected by skin cancer has been rising in recent years. Melanoma is identified as the most dangerous and life-threatening...
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Evidence-Driven Differential Diagnosis of Malignant Melanoma
We present a modular and multi-level framework for the differential diagnosis of malignant melanoma. Our framework integrates contextual information...
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Performing Melanoma Diagnosis by an Effective Multi-view Convolutional Network Architecture
Despite the proved effectiveness of deep learning models in solving complex problems, the melanoma diagnosis remains as a challenging task mainly due...
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Effective melanoma classification using inter neighbour mean order interleaved pattern on dermoscopy images
In the past few decades, the automatic melanoma classification system has been considered a dynamic and challenging research area in the field of...
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Hybrid Approach for the Design of CNNs Using Genetic Algorithms for Melanoma Classification
Melanoma is one of the most dangerous and deadly cancers in the world. In this contribution, we proposed a convolutional neural network architecture...
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Risk Stratification of Malignant Melanoma Using Neural Networks
In order to improve the detection and classification of malignant melanoma, this paper describes an image-based method that can achieve AUROC values...
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Automatic Classification of Melanoma Using Grab-Cut Segmentation & Convolutional Neural Network
BackgroundSkin diseases are common health complications around the world. One of the most unsafe types of skin cancer is melanoma. Detection of skin...
