ResNet with Integrated Convolutional Block Attention Module for Ship Classification Using Transfer Learning on Optical Satellite Imagery

arXiv:2404.02135v2 Announce Type: replace
Abstract: This study proposes a novel transfer learning framework for effective ship classification using high-resolution optical remote sensing satellite imagery. The framework is based on the deep convolutional neural network model ResNet50 and incorporates the Convolutional Block Attention Module (CBAM) to enhance performance. CBAM enables the model to attend to salient features in the images, allowing it to better discriminate between subtle differences between ships and backgrounds. Furthermore, this study adopts a transfer learning approach tailored …

abstract arxiv attention block classification convolutional neural network cs.cv eess.iv framework network neural network novel optical resnet resnet50 resolution satellite sensing ship study transfer transfer learning type