Skin Cancer Classification using Inception Network and Transfer Learning
Medical data classification is typically a challenging task due to imbalance between classes. In this paper, we propose an approach to classify dermatoscopic images from HAM10000 (Human Against Machine with 10000 training images) dataset, consisting of seven imbalanced types of skin lesions, with good precision and low resources requirements. Classification is done by using a pretrained convolutional neural network. We evaluate the accuracy and performance of the proposal and illustrate possible extensions.
Code (0)
등록된 구현이 없습니다.
Tasks
Cancer ClassificationClassificationSkin Cancer ClassificationTransfer LearningSimilar Papers 제목 키워드 기반
Multi-class Skin Cancer Classification Architecture Based on Deep Convolutional Neural Network
Skin cancer detection is challenging since different types of skin lesions share high similarities. This paper proposes a computer-based deep learning approach that will accurately identify different kinds of skin lesion…
Cancer ClassificationData AugmentationDeep LearningSkin Cancer Classification+1Skin cancer reorganization and classification with deep neural network
As one kind of skin cancer, melanoma is very dangerous. Dermoscopy based early detection and recarbonization strategy is critical for melanoma therapy. However, well-trained dermatologists dominant the diagnostic accurac…
Boundary DetectionClassificationDiagnosticGeneral Classification+5Comparative study on different Deep Learning models for Skin Lesion Classification using transfer learning approach
Developing countries, specifically India, do not have sufficient hospitals and doctors to reach out to the population. Forget about skin specialists, there are still thousands of villages without even a basic hospital. …
Lesion ClassificationSkin Lesion ClassificationTransfer LearningAutomated Skin Lesion Classification Using Ensemble of Deep Neural Networks in ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection Challenge
In this paper, we studied extensively on different deep learning based methods to detect melanoma and skin lesion cancers. Melanoma, a form of malignant skin cancer is very threatening to health. Proper diagnosis of mela…
General ClassificationLesion ClassificationSkin Lesion ClassificationSkin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks
In the last few years, Deep Learning (DL) has been showing superior performance in different modalities of biomedical image analysis. Several DL architectures have been proposed for classification, segmentation, and dete…
Cancer ClassificationClassificationGeneral ClassificationImage Segmentation+4