Latest AI and machine learning research in prescriptions for healthcare professionals.
Accurate tumor segmentation is crucial for cancer diagnosis and treatment. While foundation models have advanced general-purpose segmentation, existing methods still struggle with: (1) limited incorporation of medical priors, (2) imbalance between generic and tumor-specific features, and (3) high computational costs for clinical adaptation. To address these challenges, we propose MAST-Pro (Mixtu...
Detecting traffic signs effectively under low-light conditions remains a significant challenge. To address this issue, we propose YOLO-LLTS, an end-to-end real-time traffic sign detection algorithm specifically designed for low-light environments. Firstly, we introduce the High-Resolution Feature Map for Small Object Detection (HRFM-TOD) module to address indistinct small-object features in low-...
The clinical translation of nanoparticle-based treatments remains limited due to the unpredictability of (nanoparticle) NP pharmacokinetics$\unicode...
With the continuous emergence of various social media platforms frequently used in daily life, the multimodal meme understanding (MMU) task has been...
Digital twins (DTs) are redefining healthcare by paving the way for more personalized, proactive, and intelligent medical interventions. As the shif...
We address key limitations in existing datasets and models for task-oriented hand-object interaction video generation, a critical approach of genera...
Advertising banners are critical for capturing user attention and enhancing advertising campaign effectiveness. Creating aesthetically pleasing bann...
Vision and Language Navigation (VLN) requires an agent to navigate through environments following natural language instructions. However, existing m...
Text-to-image diffusion models have achieved remarkable success in generating high-quality contents from text prompts. However, their reliance on pu...
Effective Human-Robot Interaction (HRI) is crucial for future service robots in aging societies. Existing solutions are biased toward only well-trai...
This paper presents InteractEdit, a novel framework for zero-shot Human-Object Interaction (HOI) editing, addressing the challenging task of transfo...
Fusing LiDAR and image features in a homogeneous BEV domain has become popular for 3D object detection in autonomous driving. However, this paradigm...
Comprehensive and consistent dynamic scene understanding from camera input is essential for advanced autonomous systems. Traditional camera-based pe...
Human interaction with the external world fundamentally involves the exchange of personal memory, whether with other individuals, websites, applicat...
Accurate prediction of drug target interactions is critical for accelerating drug discovery and elucidating complex biological mechanisms. In this w...
Mental health issues among college students have reached critical levels, significantly impacting academic performance and overall wellbeing. Predic...
Hyperspectral image (HSI) and LiDAR data joint classification is a challenging task. Existing multi-source remote sensing data classification method...
The purpose of this study is to introduce SKG-LLM. A knowledge graph (KG) is constructed from stroke-related articles using mathematical and large l...
LiDAR-based 3D object detection datasets have been pivotal for autonomous driving, yet they cover a limited range of objects, restricting the model'...
While large language models (LLMs) have shown promise in diagnostic dialogue, their capabilities for effective management reasoning - including dise...