Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
The Industry 5.0 transition highlights EU efforts to design intelligent devices that can work alongside humans to enhance human capabilities, and such vision aligns with user preferences and needs to feel safe while collaborating with such systems take priority. This demands a human-centric research vision and requires a societal and educational shift in how we perceive technological advancement...
Traditional ML models utilize controlled approximations during high loads, employing faster, but less accurate models in a process called accuracy scaling. However, this method is less effective for generative text-to-image models due to their sensitivity to input prompts and performance degradation caused by large model loading overheads. This work introduces a novel text-to-image inference sys...
Given the energy constraints in autonomous mobile agents (AMAs), such as unmanned vehicles, spiking neural networks (SNNs) are increasingly favored ...
The 'keyword method' is an effective technique for learning vocabulary of a foreign language. It involves creating a memorable visual link between w...
UNet and its variants have widespread applications in medical image segmentation. However, the substantial number of parameters and computational co...
Instruction-based computer control agents (CCAs) execute complex action sequences on personal computers or mobile devices to fulfill tasks using the...
The Semantic Layered Embedding Diffusion (SLED) mechanism redefines the representation of hierarchical semantics within transformer-based architectu...
We introduce Qwen2.5-1M, a series of models that extend the context length to 1 million tokens. Compared to the previous 128K version, the Qwen2.5-1...
Key-Value (KV) cache facilitates efficient large language models (LLMs) inference by avoiding recomputation of past KVs. As the batch size and conte...
Training semantic segmenter with synthetic data has been attracting great attention due to its easy accessibility and huge quantities. Most previous...
The differentiable shift-variant filtered backprojection (FBP) model enables the reconstruction of cone-beam computed tomography (CBCT) data for any...
Magnetoencephalography (MEG) is a cutting-edge neuroimaging technique that measures the intricate brain dynamics underlying cognitive processes with...
Despite advancements in cross-domain image translation, challenges persist in asymmetric tasks such as SAR-to-Optical and Sketch-to-Instance convers...
The success of deep learning (DL) is often achieved with large models and high complexity during both training and post-training inferences, hinderi...
The Text-to-Image (T2I) diffusion model is one of the most popular models in the world. However, serving diffusion models at the entire image level ...
This work introduces a novel Retention Layer mechanism for Transformer based architectures, addressing their inherent lack of intrinsic retention ca...
Ensuring safe separation between aircraft is a critical challenge in air traffic management, particularly in urban air mobility (UAM) environments w...
Superpixel segmentation is a foundation for many higher-level computer vision tasks, such as image segmentation, object recognition, and scene under...
In the contemporary context of rapid advancements in information technology and the exponential growth of data volume, language models are confronte...
Accurate medical image segmentation is often hindered by noisy labels in training data, due to the challenges of annotating medical images. Prior re...