… this paper CNN, as a deep learning framework, is used for automatic detection of melanoma.
… Our proposed method left the process of feature extraction to CNN while traditional learning …

… for melanoma classification. Therefore, in this paper, we investigate the effectiveness of deep
features extracted from eight contemporary CNN … techniques on melanoma detection. The …

… One of the two features extractor parts is the hybrid feature … based CNN feature extractor
part. The HFE portion combines three feature extraction approaches into a single fused feature …

… detect melanoma skin cancer quickly, we can reduce human mortality rate with some initial
treatment. Currently, detection … CNN classifier used to detect whether it’s melanoma or non-…

… to identify the image regions that a CNN focuses on during its decision-… the CNN learned
features at the last layers and identified where these networks look for discriminative features. …

… question of effective usage of the feature set extracted from deep learning … melanoma
detection method based on the combination of linear discriminant analysis (LDA) and the features …

… We will extract 1000 features from each pre-trained CNN, a total of 4000 features for all the
pre-trained models. In Table 2 we compare the result of classification for the two databases …

… The Xception is described as a theory based on the Inception module that generates
cross-channels correlations and spatial relations within CNN feature maps to be entirely decoupled …

… In Figure 3, the first, second, and third block diagrams depict InceptionResNetV2, MELA-CNN,
and the optimal MM detection model proposed in this study. The overall architecture of the …

… recognition system”, which they based on deep learning method combined with “RSurf”
features and “local binary patterns” LBP.they used CNN along with SVM. They used data from …