Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Reliable localization is critical for robot navigation in complex indoor environments. In this pap...
This study presents a vision-guided robotic control system for automated fruit tree pruning applic...
3D human digitization has long been a highly pursued yet challenging task. Existing methods aim to...
Differentially Private (DP) generative marginal models are often used in the wild to release synth...
Reconstructing 3D assets from images, known as inverse rendering (IR), remains a challenging task ...
Computed tomography (CT) examination poses radiation injury to patient. A consensus performing CT ...
Loco-manipulation -- coordinated locomotion and physical interaction with objects -- remains a maj...
Scalable Vector Graphics (SVG) is an important image format widely adopted in graphic design becau...
Building precise simulations of the real world and invoking numerical solvers to answer quantitati...
Despite the span in estimating pain from facial expressions, limited works have focused on estimat...
Large-scale coreference resolution presents a significant challenge in natural language processing...
Objective: Zero-shot methodology promises to cut down on costs of dataset annotation and domain ex...
We propose an end-to-end trainable, cross-category method for reconstructing multiple man-made art...
Accurate and real-time three-dimensional (3D) pose estimation is challenging in resource-constrain...
Image retargeting aims to change the aspect-ratio of an image while maintaining its content and st...
Objective: Traditional phone-based surveys are among the most accessible and widely used methods t...
End-to-end autonomous driving has achieved remarkable progress by integrating perception, predicti...
Teleoperation plays a critical role in intuitive robot control and imitation learning, particularl...
Motivation: Building and iterating machine learning models is often a resource-intensive process. ...
In the Edge Inference (EI) paradigm, where a Deep Neural Network (DNN) is split across the transce...
Reasoning before action and imagining potential outcomes (i.e., world models) are essential for em...