TL;DR 提出CNN与ViT融合模型并通过四模型深度集成提升遥感图像分类精度。 摘要 遥感影像在许多应用中发挥着关键作用，需要精确的计算机分类技术。可靠的分类对于将原始影像转换为结构化和可用信息至关重要。虽然卷积神经网络（CNNs）主要用于图像分类 ...

Deep learning has become a transformative technology for modern weed detection, offering significant advantages over traditional machine vision in robustness, scalability, and recognition accuracy.

For neural prosthetic devices, accurate classification of high dimensional electroencephalography (EEG) signals is significantly impaired by the existence of redundant and irrelevant features that ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Abstract: This research explores a deep learning-based approach to sports image classification using four convolutional neural network (CNN) models: VGG-16, VGG-19, Xception, and EfficientNetB7. The ...

Deep learning has emerged as a transformative approach for analysing geological imagery, enabling rapid, objective interpretation of complex structures and materials across multiple scales. By ...

Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...