Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Due to network operation and maintenance relying heavily on network traffic monitoring, traffic matrix analysis has been one of the most crucial issues for network management related tasks. However, it is challenging to reliably obtain the precise measurement in computer networks because of the high measurement cost, and the unavoidable transmission loss. Although some methods proposed in recent...
Recent advances in imitation learning have shown significant promise for robotic control and embodied intelligence. However, achieving robust generalization across diverse mounted camera observations remains a critical challenge. In this paper, we introduce a video-based spatial perception framework that leverages 3D spatial representations to address environmental variability, with a focus on h...
The prevalence of multi-modal content on social media complicates automated moderation strategies. This calls for an enhancement in multi-modal clas...
Modern transformer-based deep neural networks present unique technical challenges for effective acceleration in real-world applications. Apart from ...
We show that assuming the availability of the processor with variable precision arithmetic, we can compute matrix-by-matrix multiplications in $O(N^...
In this work, we consider the problem of learning end to end perception to control for ground vehicles solely from aerial imagery. Photogrammetric s...
The precise and safe control of heavy material handling machines presents numerous challenges due to the hard-to-model hydraulically actuated joints...
We initiate a study of the geometry of the visual representation space -- the information channel from the vision encoder to the action decoder -- i...
In this paper, we present our proposed approach for active tracking to increase the autonomy of Unmanned Aerial Vehicles (UAVs) using event cameras,...
In this article, we present a novel user-centric service provision for immersive communications (IC) in 6G to deal with the uncertainty of individua...
In recent years, end-to-end autonomous driving architectures have gained increasing attention due to their advantage in avoiding error accumulation....
Objective: To improve prediction of Chronic Kidney Disease (CKD) progression to End Stage Renal Disease (ESRD) using machine learning (ML) and deep ...
While convolutional neural networks (CNNs) excel at clean image classification, they struggle to classify images corrupted with different common cor...
Water is often overused in irrigation, making efficient management of it crucial. Precision Agriculture emphasizes tools like stem water potential (...
Diabetes is a chronic disease with a significant global health burden, requiring multi-stakeholder collaboration for optimal management. Large langu...
Current open-vocabulary scene graph generation algorithms highly rely on both 3D scene point cloud data and posed RGB-D images and thus have limited...
Artificial Intelligence (AI) projects in healthcare, particularly in nursing, currently gain relevance but encounter challenges in user acceptance. Ac...
Defining and measuring decision-making styles, also known as playstyles, is crucial in gaming, where these styles reflect a broad spectrum of indivi...
To address the rural broadband challenge and to leverage the unique opportunities that rural regions provide for piloting advanced wireless applicat...
Medical imaging segmentation is a highly active area of research, with deep learning-based methods achieving state-of-the-art results in several ben...