A comprehensive survey on support vector machine classification: Applications, challenges and trends
J Cervantes, F Garcia-Lamont, L Rodríguez-Mazahua… - Neurocomputing, 2020 - Elsevier
In recent years, an enormous amount of research has been carried out on support vector
machines (SVMs) and their application in several fields of science. SVMs are one of the …
machines (SVMs) and their application in several fields of science. SVMs are one of the …
A scoping review of transfer learning research on medical image analysis using ImageNet
Objective Employing transfer learning (TL) with convolutional neural networks (CNNs), well-
trained on non-medical ImageNet dataset, has shown promising results for medical image …
trained on non-medical ImageNet dataset, has shown promising results for medical image …
[HTML][HTML] Computer-aided diagnosis for breast cancer classification using deep neural networks and transfer learning
Abstract Background and Objective: Many developed and non-developed countries
worldwide suffer from cancer-related fatal diseases. In particular, the rate of breast cancer in …
worldwide suffer from cancer-related fatal diseases. In particular, the rate of breast cancer in …
Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks
The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread
rapidly among people living in other countries and is approaching approximately …
rapidly among people living in other countries and is approaching approximately …
A novel melanoma prediction model for imbalanced data using optimized SqueezeNet by bald eagle search optimization
GI Sayed, MM Soliman, AE Hassanien - Computers in biology and …, 2021 - Elsevier
Skin lesion classification plays a crucial role in diagnosing various gene and related local
medical cases in the field of dermoscopy. In this paper, a new model for the classification of …
medical cases in the field of dermoscopy. In this paper, a new model for the classification of …
Melanoma classification using a novel deep convolutional neural network with dermoscopic images
Automatic melanoma detection from dermoscopic skin samples is a very challenging task.
However, using a deep learning approach as a machine vision tool can overcome some …
However, using a deep learning approach as a machine vision tool can overcome some …
[HTML][HTML] Superior skin cancer classification by the combination of human and artificial intelligence
Background In recent studies, convolutional neural networks (CNNs) outperformed
dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these …
dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these …
Multi-features extraction based on deep learning for skin lesion classification
For various forms of skin lesion, many different feature extraction methods have been
investigated so far. Indeed, feature extraction is a crucial step in machine learning …
investigated so far. Indeed, feature extraction is a crucial step in machine learning …
Melanoma image classification based on MobileNetV2 network
Melanoma is one of the most common types of cancer that can lead to high mortality rates if
not detected early. Recent studies about deep learning methods show promising results in …
not detected early. Recent studies about deep learning methods show promising results in …
Deep MLP-CNN model using mixed-data to distinguish between COVID-19 and Non-COVID-19 patients
The limitations and high false-negative rates (30%) of COVID-19 test kits have been a
prominent challenge during the 2020 coronavirus pandemic. Manufacturing those kits and …
prominent challenge during the 2020 coronavirus pandemic. Manufacturing those kits and …