Latest AI and machine learning research in work force for healthcare professionals.
Reflections often degrade the visual quality of images captured through transparent surfaces, and reflection removal methods suffers from the shortage of paired real-world samples.This paper proposes a hybrid approach that combines cycle-consistency with denoising diffusion probabilistic models (DDPM) to effectively remove reflections from single images without requiring paired training data. Th...
Finger vein recognition (FVR) has emerged as a secure biometric technique because of the confidentiality of vascular bio-information. Recently, deep learning-based FVR has gained increased popularity and achieved promising performance. However, the limited size of public vein datasets has caused overfitting issues and greatly limits the recognition performance. Although traditional data augmenta...
Zero-shot customized video generation has gained significant attention due to its substantial application potential. Existing methods rely on additi...
Deep generative models are proficient in generating realistic data but struggle with producing rare samples in low density regions due to their scar...
The use of CLIP embeddings to assess the alignment of samples produced by text-to-image generative models has been extensively explored in the liter...
Latent Diffusion Models (LDMs) produce high-quality, photo-realistic images, however, the latency incurred by multiple costly inference iterations c...
Retrieval augmentation, the practice of retrieving additional data from large auxiliary pools, has emerged as an effective technique for enhancing m...
"Medical deserts" are areas with low healthcare service levels, challenging the access, quality, and sustainability of care. This qualitative narrativ...
Generative AI models like GPT-4o and DALL-E 3 are reshaping digital content creation, offering industries tools to generate diverse and sophisticate...
Left-behind children (LBCs), numbering over 66 million in China, face severe mental health challenges due to parental migration for work. Early scre...
Considering the difficulty of interpreting generative model output, there is significant current research focused on determining meaningful evaluati...
The paper presents a novel Wi-Fi fingerprinting system that uses Channel State Information (CSI) data for fine-grained pedestrian localization. The ...
Graph Neural Networks (GNNs) perform effectively when training and testing graphs are drawn from the same distribution, but struggle to generalize w...
Rare diseases, despite their low individual incidence, collectively impact around 300 million people worldwide due to the vast number of diseases. T...
Software engineering (SE) faces significant diversity challenges in both academia and industry, with underrepresented students encountering hostile ...
Domain Generalized Semantic Segmentation (DGSS) seeks to utilize source domain data exclusively to enhance the generalization of semantic segmentati...
Existing work on large language model (LLM) personalization assigned different responding roles to LLM, but overlooked the diversity of questioners....
The use of machine learning to estimate the energy of a group of atoms, and the forces that drive them to more stable configurations, have revolutio...
Data-free knowledge distillation transfers knowledge by recovering training data from a pre-trained model. Despite the recent success of seeking glo...
Estimating physical properties for visual data is a crucial task in computer vision, graphics, and robotics, underpinning applications such as augme...