Research graph
References from DERMIS: An explainable dual-branch ensemble framework for robust melanoma detection. Local targets link to admitted publications; unresolved targets remain external evidence.
SHERA: SHAP-enhanced resource allocation for VM scheduling and efficient cloud computing
10.1109/access.2025.3568917 · 2025 · External reference
An interpretable skin cancer classification using optimized convolutional neural network for a smart healthcare system
10.1109/access.2023.3269694 · 2023 · External reference
A hybrid deep learning approach for skin cancer classification using swin transformer and dense group shuffle non-local attention network
10.1109/access.2024.3485507 · 2024 · External reference
The power of generative AI to augment for enhanced skin cancer classification: A deep learning approach
10.1109/access.2023.3332628 · 2023 · External reference
An attention-based mechanism to combine images and metadata in deep learning models applied to skin cancer classification
10.1109/jbhi.2021.3062002 · 2021 · External reference
Handheld microwave system for in vivo skin cancer detection: Development and clinical validation
10.1109/tim.2024.3398123 · 2024 · External reference
A mutual bootstrapping model for automated skin lesion segmentation and classification
10.1109/tmi.2020.2972964 · 2020 · External reference
Early detection of multiclass skin lesions using transfer learning-based incepX-Ensemble model
10.1109/access.2024.3432904 · 2024 · External reference
Towards improving skin cancer diagnosis by integrating microarray and RNA-seq datasets
10.1109/jbhi.2019.2953978 · 2020 · External reference
FCN-based DenseNet framework for automated detection and classification of skin lesions in dermoscopy images
10.1109/access.2020.3016651 · 2020 · External reference
Multi-class skin lesion detection and classification via teledermatology
10.1109/jbhi.2021.3067789 · 2021 · External reference
Enhancing cervical cancer classification: Through a hybrid deep learning approach integrating DenseNet201 and InceptionV3
10.1109/access.2025.3527677 · 2025 · External reference
Noninvasive real-time automated skin lesion analysis system for melanoma early detection and prevention
10.1109/jtehm.2015.2419612 · 2015 · External reference
Classification of melanoma and nevus in digital images for diagnosis of skin cancer
10.1109/access.2019.2926837 · 2019 · External reference
DeepSkin: A deep learning approach for skin cancer classification
10.1109/access.2023.3274848 · 2023 · External reference
Four-class classification of skin lesions with task decomposition strategy
10.1109/tbme.2014.2348323 · 2015 · External reference
Region-of-interest based transfer learning assisted framework for skin cancer detection
10.1109/access.2020.3014701 · 2020 · External reference
DCENSnet: A new deep convolutional ensemble network for skin cancer classification
10.1016/j.bspc.2023.105757 · 2024 · External reference
A GAN-based data augmentation method for imbalanced multi-class skin lesion classification
10.1109/access.2024.3360215 · 2024 · External reference
Melanoma is skin deep: A 3D reconstruction technique for computerized dermoscopic skin lesion classification
10.1109/jtehm.2017.2648797 · 2017 · External reference
Unit-vise: Deep shallow unit-vise residual neural networks with transition layer for expert level skin cancer classification
10.1109/tcbb.2020.3039358 · 2022 · External reference
FixCaps: An improved capsules network for diagnosis of skin cancer
10.1109/access.2022.3181225 · 2022 · External reference
CHASHNIt for enhancing skin disease classification using GAN augmented hybrid model with LIME and SHAP based XAI heatmaps
10.1038/s41598-025-13647-3 · 2025 · External reference
Hybrid convolutional neural networks with SVM classifier for classification of skin cancer
10.1016/j.bea.2022.100069 · 2023 · External reference
Classification of human skin cancer using Stokes-Mueller decomposition method and artificial intelligence models
10.1016/j.ijleo.2021.168239 · 2022 · External reference
Web-based skin cancer assessment and classification using machine learning and mobile computerized adaptive testing in a Rasch model: Development study
10.2196/33006 · 2022 · External reference
Genetic programming for automatic skin cancer image classification
10.1016/j.eswa.2022.116680 · 2022 · External reference
Categorical classification of skin cancer using a weighted ensemble of transfer learning with test time augmentation
2024 · External reference
A full-resolution convolutional network with a dynamic graph cut algorithm for skin cancer classification and detection
2023 · External reference
Machine learning-based classification of skin cancer hyperspectral images
10.1016/j.procs.2023.10.278 · 2023 · External reference
Augmented intelligence enabled deep neural networking framework for skin cancer classification and prediction using multi-dimensional datasets on industrial IoT standards
10.1016/j.micpro.2023.104755 · 2023 · External reference
Skin cancer classification using explainable artificial intelligence on pre-extracted image features
2023 · External reference
A genetic programming approach with adaptive region detection to skin cancer image classification
2024 · External reference
An instrument for accurate and non-invasive screening of skin cancer based on multimodal imaging
10.1109/access.2019.2956898 · 2019 · External reference
Towards improving skin cancer diagnosis by integrating dermoscopic images and metadata
2020 · External reference
Skin cancer classification based on a hybrid deep model and long short-term memory
10.1016/j.bspc.2024.107109 · 2025 · External reference
Automated skin cancer classification and detection using convolutional neural networks and dermoscopy images
10.1016/j.procs.2024.12.012 · 2025 · External reference
Double AMIS-ensemble deep learning for skin cancer classification
10.1016/j.eswa.2023.121047 · 2023 · External reference
Transfer learning for segmentation with hybrid classification to detect melanoma skin cancer
10.1016/j.heliyon.2023.e15416 · 2023 · External reference
Skin cancer classification using AI for mobile applications
2023 · External reference
Hybrid deep learning model combining LSTM and ResNet50 for skin cancer classification
10.1016/j.bspc.2024.107109 · 2025 · External reference
AI-driven lesion segmentation models for improved skin cancer classification
2023 · External reference
10.1109/i-pact65952.2025.11308059
10.1109/i-pact65952.2025.11308059 · External reference
Unresolved reference
2022 · External reference
Hybrid convolutional neural networks with SVM classifier for classification of skin cancer
10.1016/j.bea.2022.100069 · ExternalCitation · doi-reference
DCENSnet: A new deep convolutional ensemble network for skin cancer classification
10.1016/j.bspc.2023.105757 · ExternalCitation · doi-reference
Hybrid deep learning model combining LSTM and ResNet50 for skin cancer classification
10.1016/j.bspc.2024.107109 · ExternalCitation · doi-reference
Genetic programming for automatic skin cancer image classification
10.1016/j.eswa.2022.116680 · ExternalCitation · doi-reference
Double AMIS-ensemble deep learning for skin cancer classification
10.1016/j.eswa.2023.121047 · ExternalCitation · doi-reference
Transfer learning for segmentation with hybrid classification to detect melanoma skin cancer
10.1016/j.heliyon.2023.e15416 · ExternalCitation · doi-reference
Classification of human skin cancer using Stokes-Mueller decomposition method and artificial intelligence models
10.1016/j.ijleo.2021.168239 · ExternalCitation · doi-reference
Augmented intelligence enabled deep neural networking framework for skin cancer classification and prediction using multi-dimensional datasets on industrial IoT standards
10.1016/j.micpro.2023.104755 · ExternalCitation · doi-reference
Machine learning-based classification of skin cancer hyperspectral images
10.1016/j.procs.2023.10.278 · ExternalCitation · doi-reference
Automated skin cancer classification and detection using convolutional neural networks and dermoscopy images
10.1016/j.procs.2024.12.012 · ExternalCitation · doi-reference
CHASHNIt for enhancing skin disease classification using GAN augmented hybrid model with LIME and SHAP based XAI heatmaps
10.1038/s41598-025-13647-3 · ExternalCitation · doi-reference
Classification of melanoma and nevus in digital images for diagnosis of skin cancer
10.1109/access.2019.2926837 · ExternalCitation · doi-reference
An instrument for accurate and non-invasive screening of skin cancer based on multimodal imaging
10.1109/access.2019.2956898 · ExternalCitation · doi-reference
Region-of-interest based transfer learning assisted framework for skin cancer detection
10.1109/access.2020.3014701 · ExternalCitation · doi-reference
FCN-based DenseNet framework for automated detection and classification of skin lesions in dermoscopy images
10.1109/access.2020.3016651 · ExternalCitation · doi-reference
FixCaps: An improved capsules network for diagnosis of skin cancer
10.1109/access.2022.3181225 · ExternalCitation · doi-reference
An interpretable skin cancer classification using optimized convolutional neural network for a smart healthcare system
10.1109/access.2023.3269694 · ExternalCitation · doi-reference
DeepSkin: A deep learning approach for skin cancer classification
10.1109/access.2023.3274848 · ExternalCitation · doi-reference
The power of generative AI to augment for enhanced skin cancer classification: A deep learning approach
10.1109/access.2023.3332628 · ExternalCitation · doi-reference
A GAN-based data augmentation method for imbalanced multi-class skin lesion classification
10.1109/access.2024.3360215 · ExternalCitation · doi-reference
Early detection of multiclass skin lesions using transfer learning-based incepX-Ensemble model
10.1109/access.2024.3432904 · ExternalCitation · doi-reference
A hybrid deep learning approach for skin cancer classification using swin transformer and dense group shuffle non-local attention network
10.1109/access.2024.3485507 · ExternalCitation · doi-reference
Enhancing cervical cancer classification: Through a hybrid deep learning approach integrating DenseNet201 and InceptionV3
10.1109/access.2025.3527677 · ExternalCitation · doi-reference
SHERA: SHAP-enhanced resource allocation for VM scheduling and efficient cloud computing
10.1109/access.2025.3568917 · ExternalCitation · doi-reference
10.1109/i-pact65952.2025.11308059
10.1109/i-pact65952.2025.11308059 · ExternalCitation · doi-reference
Towards improving skin cancer diagnosis by integrating microarray and RNA-seq datasets
10.1109/jbhi.2019.2953978 · ExternalCitation · doi-reference
An attention-based mechanism to combine images and metadata in deep learning models applied to skin cancer classification
10.1109/jbhi.2021.3062002 · ExternalCitation · doi-reference
Multi-class skin lesion detection and classification via teledermatology
10.1109/jbhi.2021.3067789 · ExternalCitation · doi-reference
Noninvasive real-time automated skin lesion analysis system for melanoma early detection and prevention
10.1109/jtehm.2015.2419612 · ExternalCitation · doi-reference
Melanoma is skin deep: A 3D reconstruction technique for computerized dermoscopic skin lesion classification
10.1109/jtehm.2017.2648797 · ExternalCitation · doi-reference
Four-class classification of skin lesions with task decomposition strategy
10.1109/tbme.2014.2348323 · ExternalCitation · doi-reference
Unit-vise: Deep shallow unit-vise residual neural networks with transition layer for expert level skin cancer classification
10.1109/tcbb.2020.3039358 · ExternalCitation · doi-reference
Handheld microwave system for in vivo skin cancer detection: Development and clinical validation
10.1109/tim.2024.3398123 · ExternalCitation · doi-reference
A mutual bootstrapping model for automated skin lesion segmentation and classification
10.1109/tmi.2020.2972964 · ExternalCitation · doi-reference
Web-based skin cancer assessment and classification using machine learning and mobile computerized adaptive testing in a Rasch model: Development study
10.2196/33006 · ExternalCitation · doi-reference
