Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
The role of mental simulation in human physical reasoning is widely acknowledged, but whether it is employed across scenarios with varying simulation costs and where its boundary lies remains unclear. Using a pouring-marble task, our human study revealed two distinct error patterns when predicting pouring angles, differentiated by simulation time. While mental simulation accurately captured huma...
Recently, reconstructing scenes from a single panoramic image using advanced 3D Gaussian Splatting (3DGS) techniques has attracted growing interest. Panoramic images offer a 360$\times$ 180 field of view (FoV), capturing the entire scene in a single shot. However, panoramic images introduce severe distortion, making it challenging to render 3D Gaussians into 2D distorted equirectangular space di...
In image fusion tasks, the absence of real fused images as priors presents a fundamental challenge. Most deep learning-based fusion methods rely on ...
This study proposes a medical entity extraction method based on Transformer to enhance the information extraction capability of medical literature. ...
Support Vector Machine (SVM) is a popular supervised classification model that works by first finding the margin boundaries for the training data cl...
We present NUPunkt and CharBoundary, two sentence boundary detection libraries optimized for high-precision, high-throughput processing of legal tex...
Inverse problems for partial differential equations (PDEs) are crucial in numerous applications such as geophysics, biomedical imaging, and material...
The accurate delineation of agricultural field boundaries from satellite imagery is vital for land management and crop monitoring. However, current ...
Depth completion, which estimates dense depth from sparse LiDAR and RGB images, has demonstrated outstanding performance in well-lit conditions. How...
Accurate segmentation of polyps and skin lesions is essential for diagnosing colorectal and skin cancers. While various segmentation methods for pol...
Cross-layer feature pyramid networks (CFPNs) have achieved notable progress in multi-scale feature fusion and boundary detail preservation for salie...
This paper proposes a visual encryption method to ensure the confidentiality of digital images. The model used is based on an autoencoder using aCon...
3D intraoral scan mesh is widely used in digital dentistry diagnosis, segmenting 3D intraoral scan mesh is a critical preliminary task. Numerous app...
Semi-supervised semantic segmentation (SS-SS) aims to mitigate the heavy annotation burden of dense pixel labeling by leveraging abundant unlabeled ...
As a fundamental task in computer vision, semantic segmentation is widely applied in fields such as autonomous driving, remote sensing image analysi...
Malicious image manipulation poses societal risks, increasing the importance of effective image manipulation detection methods. Recent approaches in...
Reconstructing precise camera poses and floor plan layouts from wide-baseline RGB panoramas is a difficult and unsolved problem. We introduce BADGR,...
Classically, to solve differential equation problems, it is necessary to specify sufficient initial and/or boundary conditions so as to allow the ex...
Segment Anything Model (SAM) demonstrates powerful zero-shot capabilities; however, its accuracy and robustness significantly decrease when applied ...
Due to the limited accuracy of 4D Magnetic Resonance Imaging (MRI) in identifying hemodynamics in cardiovascular diseases, the challenges in obtaini...