arXiv:2303.10894v3 Announce Type: replace
Abstract: Accurate medical image segmentation is critical for early medical diagnosis. Most existing methods are based on U-shape structure and use element-wise addition or concatenation to fuse different leve…
arXiv:2604.10245v1 Announce Type: new
Abstract: Registration between preoperative CT and intraoperative laparoscopic video plays a crucial role in augmented reality (AR) guidance for minimally invasive surgery. Learning-based methods have recently ach…
arXiv:2502.18026v3 Announce Type: replace
Abstract: Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging task and often requires downstream analyses and specialize…
arXiv:2510.15282v2 Announce Type: replace-cross
Abstract: Magnetic Resonance Imaging (MRI) is the primary imaging modality used in the diagnosis, assessment, and treatment planning for brain pathologies. However, most automated MRI analysis tools, suc…
arXiv:2512.19049v2 Announce Type: replace
Abstract: Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control. Existing approaches often require manually specifi…
arXiv:2407.08101v4 Announce Type: replace
Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, where each turn must be stepped (i.e., prompted) by the…
arXiv:2603.13941v2 Announce Type: replace
Abstract: Growing waste streams and the transition to a circular economy require efficient automated waste sorting. In industrial settings, materials move on fast conveyor belts, where reliable identification …
arXiv:2604.09635v1 Announce Type: cross
Abstract: This study develops machine learning models to assess Media and Information Literacy (MIL) skills specifically in the context of disinformation among students, particularly future educators and communi…
arXiv:2604.10219v1 Announce Type: new
Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved remarkable strides in visual reasoning through test time compute scaling, yet long chain reasoning remains prone to hallucinations. We identify a c…
arXiv:2604.11402v1 Announce Type: new
Abstract: Scene change detection (SCD) is crucial for urban monitoring and navigation but remains challenging in real-world environments due to lighting variations, seasonal shifts, viewpoint differences, and comp…