… in machine learning techniques in the extraction of features and classification of images as
… The main contribution of this research work is a classification framework that can distinguish …

… machine learning algorithms for the purpose of classification, and … to the subgroup of machine
learning—deep learning, ie, … both the feature extraction and classification in one algorithm. …

… Convolutional neural network is an effective machine learning technique from the deep
learning and it is similar to ordinary Neural Networks. Convolutional neural network is a network …

… the utilization of machine learning and deep learning-based … vector machine’, ‘feedforward
artificial neural network’, ‘deep … types of skin cancer - Basal Cell Carcinoma and Melanoma …

… learning methods like the Resnet model. An application of machine learning with a focus
on skin cancer … Pre-processing, segmentation, feature extraction, and classification are all …

… carcinoma and basal cell carcinoma. Non-melanoma skin cancer is the 5th most frequently
occurring cancer, … to develop a skin cancer detection CNN model which can classify the skin …

… , a deep learning network has been selected and trained by the author for the analysis of
more than 24,000 skin cancer … the best architectures in the classification of these images and …

… an automated classification of malignant and benign skin cancer based on the hybrid method
of deep learning. The proposed method is based on stacking the classification model into …

… of deep learning concepts [5], we can classify skin cancer … cell carcinoma, actinic keratosis,
vascular lesions, and dermatofibroma. Generally, a dermatologist specializing in skin cancer …

… The objective of this study is to leverage the capabilities of DL for the classification of skin
cancer. We utilized a dataset of 3000 images collected from the field, encompassing nine …