Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
As the dependence on satellite imaging continues to grow, modern satellites have become increasingly...
Object detectors often perform well in-distribution, yet degrade sharply on a different benchmark. W...
The utilization of cellulose derivatives offers an eco-friendly alternative to petroleum-based polym...
Long-term continuous monitoring of volatile organic compounds (VOCs) is pivotal for climate change r...
The accurate characterization of the potential energy surface (PES) is fundamental to understanding ...
Current AI advances largely rely on scaling neural models and expanding training datasets to achie...
We conduct an extensive study on the state of calibration under real-world dataset shift for image...
Advances in low-communication training algorithms are enabling a shift from centralised model trai...
Decoding speech from brain signals is a challenging research problem. Although existing technologi...
Precise Event Spotting (PES) in sports videos requires frame-level recognition of fine-grained act...
Image fusion aims to integrate complementary information across modalities to generate high-qualit...
Text-to-image diffusion models (T2I DMs), represented by Stable Diffusion, which generate highly r...
Text-to-image diffusion models (T2I DMs), represented by Stable Diffusion, which generate highly r...
Objective: Latent diffusion models (LDMs) could mitigate data scarcity challenges affecting machin...
Despite the success of deep learning across various domains, it remains vulnerable to adversarial ...
Composed Image Retrieval (CIR) represents a novel retrieval paradigm that is capable of expressing...
PURPOSE: Development of aphasia therapies is limited by clinician shortages, patient recruitment cha...
Ethereum smart contracts operate in a concurrent environment where multiple transactions can be su...
Large Language Models (LLMs) have become an essential infrastructure for Artificial General Intell...
Graph convolutional networks (GCNs) are fundamental in various scientific applications, ranging fr...
Emerging low-altitude economy networks (LAENets) require agile and privacy-preserving resource con...