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: In the task of text classification, the method based on large model has gradually replaced base model. However, in the case of insufficient computing resources, fine-tuning operations are ...

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: Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. This study applies ...

Abstract: Short text classification is one of the core tasks in the field of natural language processing, which has attracted extensive attention due to problems such as semantic sparsity and ...

Abstract: Tire-road friction coefficient information is an essential factor in the driving stability and safety of a vehicle. In recent years, there has been a lot of research on using the vibration ...

Abstract: NLP, an AI field, that allows communication between computers and humans. NLP news text classification uses machine learning to categorize news into predefined groups. The vast volume of ...

Abstract: The approach we offer makes use of CNN, attention methods and SVM to develop a combined framework that reaches higher performance. Attention mechanisms and CNN networks are used by this ...

Dec 18 (Reuters) - The U.S. Department of Health and Human Safety is planning to overhaul its childhood vaccine schedule to recommend fewer shots, CNN reported on Thursday. The department did not ...

Abstract: The Internet of Things (IoT) ecosystem has attracted widespread attention worldwide because of its profound commercial, economic, and social impact on the daily lives of human beings.