Publication Type : Conference Paper
Publisher : Springer Nature Switzerland
Source : Communications in Computer and Information Science
Url : https://doi.org/10.1007/978-3-031-53085-2_13
Campus : Amaravati
School : School of Computing
Year : 2024
Abstract : Skin cancer prediction has become an essential task in dermoscopic image analysis. For automatic diagnosis of the skin lesions, the Scientific community. The most crucial part in the cure of skin cancer is the exact identification and classification of the skin lesion types. This paper proposes a modified snapshot ensemble algorithm for skin lesion classification. This method utilizes the advantages of transfer learning approach with ResNet50. The method is shown efficient results for the popular metrics, such as accuracy, F1-score, recall and precision.
Cite this Research Publication : Samson Anosh Babu Parisapogu, Mastan Mohammed Meera Durga, Vallela Kaushik Shashank Reddy, Boyapati Kalyan Chakravarthi, P. Vasanth Sena, Modified Snapshot Ensemble Algorithm for Skin Lesion Classification, Communications in Computer and Information Science, Springer Nature Switzerland, 2024, https://doi.org/10.1007/978-3-031-53085-2_13