Res-DSCBAM: A Comprehensive Framework for Efficient Oil Palm Pest Classification Using Integrated ResNet50, Depthwise Separable Convolution, and Convolutional Block Attention Module. | EBSCOhost

Connecting you to content on EBSCOhost

Title: Res-DSCBAM: A Comprehensive Framework for Efficient Oil Palm Pest Classification Using Integrated ResNet50, Depthwise Separable Convolution, and Convolutional Block Attention Module.
Authors: Muhathir; Lubis, Andre Hasudungan; Wardani, Dwika Karima; Pradana, Mahardika Gama
Publication: IAENG International Journal of Computer Science, 2025, Vol 52, Issue 1, p244
ISSN: 1819-656X
Publication type: Academic Journal