A new study presents a deep learning approach for IoT malware detection in EV charging stations, addressing key limitations ...

A new study maps the rapidly evolving field of intelligent colonoscopy. It argues that the next leap will come not from isolated-task modeling alone ...

Tracking land cover over long time periods is essential for understanding climate, ecosystems, and human development, yet many annual maps are inconsistent from year to year. This study presents a new ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

In the lush, misty valleys of southwest China, satellite imagery reveals the country’s accelerating nuclear buildup, a force designed for a new age of superpower rivalry. One such valley is known as ...

Abstract: Deep learning has emerged as a critical paradigm in hyperspectral image (HSI) classification, addressing the inherent challenges posed by high-dimensional data and limited labeled samples.

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 ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...

Intervertebral disc anomalies, such as degeneration and herniation, are common causes of spinal disorders, often leading to chronic pain and disability. Accurate diagnosis and classification of these ...

This study aimed to develop a hybrid deep learning model for classifying multiple fundus diseases using ultra-widefield (UWF) images, thereby improving diagnostic efficiency and accuracy while ...