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 ...

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 ...

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 ...

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...

Microplastics have been found to be highly pervasive in the environment, driving concerns for health, environment, and ecology. Analytical methods that can accurately identify microplastics are ...

Abstract: We conduct image differentiation between benignancy and malignancy for ultrasonography image of thyroid, and also classification of false positive reduction from true positive mass of ...