… Within the scope of this study, a Convolutional Neural Network (CNN) model for the diagnosis
of skin cancer was created, constructed, and evaluated using a well-known melanoma …

… The dataset plays a crucial role in the training of our proposed neural networks for
automated diagnosis. The dataset named HAM10000 is the skin disease dataset that has been …

… In this paper, we extracted the different skin disease images in DermNet database and classify
the diseases by using convolutional neural network architecture. The major skin diseases …

… disease taxonomy. We trained state-of-the-art Deep Neural Networks on two of the largest
publicly available skin … ISIC Archive, and also leveraged disease taxonomy, where available, …

… CAD system for skin diseases' detection is still challenging research problem. In this paper,
unique skin disease identification was proposed for three types of skin diseases such as …

… skin disease problem. Moreover, most of the existing works in skin disease used convolutional
neural networks (… model to learn discriminative features from skin images. Thus to address …

… Skin diseases are a serious hazard to … skin diseases diagnosis. In this work, Deep learning
algorithms Convolution Neural Networks (CNN) is proposed to classify skin diseases on the …

… In this paper, we applied deep neural network algorithm to classify dermoscopic images of
four common skin diseases and archived promising results. Based on the results, we further …

… skin diseases using digital images of skin is very important for bio-medical image analysis. …
artificial neural network has been proposed to classify images. Here 3 common skin diseases …

… neural network for Skin Disease Diagnosis (SDD) based on patients’ symptoms and causative
organisms. The artificial neural network … diagnosing selected skin diseases in the tropical …