Deep Learning-Based Transfer Learning for Classification of Skin Cancer

Cited by (176)

Items 101–176 of 176

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16. A Comprehensive Study on Pre-trained Models for Skin Lesion Diagnosis in a Federated Setting
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17. Multimodal Skin Cancer Classification: Optimized Convolutional Network with Customized Loss and RNN-Based FCNN Fusion
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18. Skin Cancer Detection Using Image Classification in Deep Learning
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19. Multiscale Dynamic Attention Framework for Skin Lesion Segmentation and Classification
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20. Efficiency Evaluation of Hanning Window-based Filter on Human Skin Disease Diagnosis
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21. Skin cancer diagnosis using artificial intelligence methods: a review of the most recent research
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22. Convolution Neural Network Models to Detect Melanoma: A Review
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23. Comparing Skin Cancer Diagnosis between manual, 4 classical, and 1 deep machine learning algorithms
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24. A Novel Skin and Mole Pattern Identification Using Deep Residual Pooling Network (DRPN)
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25. An Ensemble Learning Approach For Improved Skin Cancer Classification
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26. A Review on the Skin Cancer Detection Using Deep Learning Algorithms and LBP
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30. Machine Learning Neural Network Classifier Interfaced Skin Cancer Identification for Medical Diagnosis System
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33. Comparitive Analysis Of Deep Learning Techniques For Prediction of Complex Skin Cancer
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34. Real-Time Dermatological Classification and Knowledge Retrieval: A Deep Learning and Web Scraping Approach
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35. Blockchain-Based Skin Cancer Detection: Enhancing Accuracy and Security with DHETL
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36. Deep Learning-Based Techniques for Detection of Cancer
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37. Comparative Study Of Gradient Optimizers For Enhanced Skin Cancer Image Analysis
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38. Skin Lesion Hybrid Classification and Segmentation Based on Extracted Deep Features
    Aboubakr Aakaou, Karl Thurnhofer‐Hemsi, Enrique Domínguez · 2025 · Lecture notes in computer science
39. Fairness Matters: Evaluating and Mitigating Bias in Skin Cancer Classification
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40. Systematic Review for the Automatic Image Classification of Skin Cancer Based on Machine Learning Techniques
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41. A Comparative Analysis of Pre-Trained CNN Models for Skin Cancer Classification
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42. FLAG-Net: Classification of Skin Lesions with a Hybrid Deep Learning Approach Based on Fractals and Lacunarity
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43. Unveiling Skin Cancer: A Review of Deep Learning Techniques for Detection
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44. Skin Cancer Classification Using Hybrid Deep Learning Approaches
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45. Xceptionderm: Deep transfer learning-based skin cancer detection
    Bhageshwari Ratkal, Khatija Unnisa, Mandakini Chagamreddy, Reddygari Pallavi Reddy, Nagaraju Krishna Chythanya, Mudigonda Rathna Chary, Laith H. Jasim · 2025 · AIP conference proceedings
46. Progressive Defocusing Guided Attention in a Hybrid CNN-Transformer CADx System for Skin Lesion Classification
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47. Melanoma classification using ensemble deep transfer learning
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48. Deep Learning Based Dog SkinPrediction: A Multi Label Classification Approach using Resent18
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49. A Deep Learning-Based Method for Skin Cancer Detection
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50. Melanoma Cancer Detection Using Deep Learning
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51. A Comprehensive Approach to Skin Lesion Classification Using Machine and Deep Learning
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52. Deep Learning-Based Detection of Skin and Oral Cancer: Advancing Diagnostic Accuracy and Early Intervention
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53. DermaCare: A Hybrid Ensemble Deep Learning System for Skin Cancer Classification and Post-Treatment Recovery Monitoring
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54. Quantum-Inspired Algorithms for Enhanced Skin Analysis in Dermatology
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55. F2M: Improving Skin Disease Recognition by Fusing Multi-Source and Multi-Scale Image Features
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56. Cross-cancer survival prediction using machine learning models
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57. RRDN Meets Deep CNNs: A Unified Approach to High-Precision Skin Cancer Classification
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58. ML-Based Medical diagnosis for skin disease
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59. Advancing Skin Cancer Detection Using DenseNet with Data Augmentation Strategies
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60. Dermatology: The Ideal Field for A.I. to Thrive
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66. Contrast-Focused Preprocessing for Skin Lesion Segmentation and Classification
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68. Computational Detection of Pigmented Skin Cancer Images Using Machine Learning and Optimization Techniques
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69. The Effect of the Label Smoothing Parameter on the Performance of a Lightweight Convolutional Neural Network-Based Model in Skin Lesion Classification
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70. Federated Learning for Skin Lesion Classification: An Attention-Enhanced EfficientNetV2 with Advanced weighted Aggregation
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71. GSARC: a group shuffle activated redundant connection framework for post-hoc feature space adaptation in skin lesion classification on the HAM10000 dataset
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73. SA-NET: A Self-attention Approach for Early and Accurate Skin Cancer Diagnosis Toward Intelligent Dermatology
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