Melanoma detection by analysis of clinical images using convolutional neural network
… 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 …
… Our proposed method left the process of feature extraction to CNN while traditional learning …
A comprehensive analysis of dermoscopy images for melanoma detection via deep CNN features
… for melanoma classification. Therefore, in this paper, we investigate the effectiveness of deep
features extracted from eight contemporary CNN … techniques on melanoma detection. The …
features extracted from eight contemporary CNN … techniques on melanoma detection. The …
Hybrid feature fusion and machine learning approaches for melanoma skin cancer detection
… 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 …
part. The HFE portion combines three feature extraction approaches into a single fused feature …
[HTML][HTML] Proposing a hybrid technique of feature fusion and convolutional neural network for melanoma skin cancer detection
… 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-…
treatment. Currently, detection … CNN classifier used to detect whether it’s melanoma or non-…
Exploring the correlation between deep learned and clinical features in melanoma detection
T Chowdhury, ARS Bajwa, T Chakraborti… - … and Analysis: 25th …, 2021 - Springer
… 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. …
features at the last layers and identified where these networks look for discriminative features. …
Optimised deep learning features for improved melanoma detection
T Majtner, S Yildirim-Yayilgan… - Multimedia Tools and …, 2019 - Springer
… 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 …
detection method based on the combination of linear discriminant analysis (LDA) and the features …
Efficient fusion of handcrafted and pre-trained CNNs features to classify melanoma skin cancer
… 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 …
pre-trained models. In Table 2 we compare the result of classification for the two databases …
Deep Learning‐Based Classification for Melanoma Detection Using XceptionNet
X Lu… - Journal of Healthcare …, 2022 - Wiley Online Library
… 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 …
cross-channels correlations and spatial relations within CNN feature maps to be entirely decoupled …
Melanoma detection using XGB classifier combined with feature extraction and K-means SMOTE techniques
… 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 …
and the optimal MM detection model proposed in this study. The overall architecture of the …
Study of melanoma detection and classification techniques
A Gupta, S Thakur, A Rana - 2020 8th International conference …, 2020 - ieeexplore.ieee.org
… 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 …
features and “local binary patterns” LBP.they used CNN along with SVM. They used data from …
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