Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...

The YOLOv8 and Swin Transformer dual-module system significantly improves structural crack detection, offering a faster and more accurate inspection method.

This study presents a solar-powered robot integrating AI and IoT for real-time plant disease detection, offering a scalable ...

Abstract: Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) are critical for effective diagnosis and treatment planning. This paper proposes a novel ...

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 ...

1 Department of General Surgery, Shangyu People’s Hospital of Shaoxing, Shaoxing, Zhejiang, China 2 Center of Gallbladder Disease, Shanghai East Hospital, Institute of Gallstone Disease, School of ...

Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, India Introduction: Colorectal cancer (CRC) remains one of the leading causes of cancer-related deaths ...

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 ...

Abstract: Road segmentation is a key task in remote sensing semantic segmentation, and the existing deep learning methods still have the problems of insufficient fineness, difficulty in modeling ...

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...

ABSTRACT: Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving ...