Abstract: With the application of massive wireless devices, the receiver often receives mixed signals with time-frequency overlapping. Automatic modulation classification (AMC) of such mixed signals ...

Accurate monitoring of water resources is essential for disaster risk reduction and sustainable development amid global climate change. At present, various methods based on convolutional neural ...

Abstract: Explainable Artificial Intelligence (XAI) has emerged as a critical tool for interpreting the predictions of complex deep learning models. While XAI has been increasingly applied in various ...

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Abstract: Convolutional neural networks (CNNs) have been foundational in deep learning architectures for image processing, and recently, Transformer networks have emerged, bringing further ...

Abstract: Enterprises often maintain large volumes of scanned documents and images that contain critical data vital for driving organizational growth and success. In the finance sector, for example, ...

Abstract: Acute Lymphoblastic Leukemia (ALL) is a serious blood cancer characterized by the abnormal growth of progenitor white blood cells, which interferes with normal blood cell production. Early ...

Abstract: Fiber Bragg Grating (FBG) sensing systems have demonstrated strong potential for distributed vibration monitoring, yet recognizing mixed intrusion events remains challenging due to the ...

ASAP scheduling uses the greedy algorithm, which is also similar to the Maximum Matching at each time TICK.

Abstract: Depression is a prevalent mental disorder that involves prolonged feelings of sadness or loss of interest in activities for a long time, even self-harm and suicidal. However, due to low ...

Abstract: Cardiac auscultation is a key non-invasive heart disease diagnostic method, but traditional heart sound diagnosis depends highly on physicians' experience, with subjective bias. Deep ...