Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
Abstract: Knowledge distillation (KD) has recently demonstrated remarkable potential in developing lightweight convolutional neural networks for remote sensing image (RSI) scene classification tasks.
Abstract: This study aimed to design and evaluate a fusion deep learning architecture (SwinCNN + OE) for robust and interpretable breast cancer classification using histopathological images. The ...
Abstract: Fine-grained flower image classification (FGFIC) is challenging due to high similarities among species and variations within species, especially with limited training data. Existing genetic ...
Abstract: Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. This study applies ...
Abstract: Hybrid convolutional neural networks (CNNs) and Transformer-based architectures have demonstrated strong potential in histopathological image analysis by combining local feature extraction ...
Abstract: Online image super-resolution (SR) services have been widely used in applications such as Remini and DeepAI. However, the exposure of plaintext images raises serious privacy concerns. While ...
Kasie Hunt talks to Rep. Suhas Subramanyam after Democrats on the House Oversight Committee release more images from the Epstein estate. The panel discusses what Indiana Republicans' rejection of ...
CNN's Jake Tapper wrongly identifies DC pipe bomb suspect as 'White man' Fox News senior national correspondent Kevin Corke reports on the arrest of the alleged Jan. 6th pipe bomb suspect on ‘Jesse ...
Abstract: In this paper, we propose a lightweight privacy-preserving convolutional neural network framework for military vehicle images classification (LPP-CNN). Existing target classification methods ...
Plant and leaf diseases have a significant impact on agricultural production, leading to a decrease in crop yield and quality. Effective crop management demands early and precise detection of the ...
Abstract: In hyperspectral image (HSI) classification, Transformer and CNN are widely used because they complement each other in extracting features. Nevertheless, existing Transformer-based methods ...