Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
The prevalence of multi-modal content on social media complicates automated moderation strategies. This calls for an enhancement in multi-modal classification and a deeper understanding of understated meanings in images and memes. Although previous efforts have aimed at improving model performance through fine-tuning, few have explored an end-to-end optimization pipeline that accounts for modali...
Modern transformer-based deep neural networks present unique technical challenges for effective acceleration in real-world applications. Apart from the vast amount of linear operations needed due to their sizes, modern transformer models are increasingly reliance on precise non-linear computations that make traditional low-bitwidth quantization methods and fixed-dataflow matrix accelerators inef...
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...
This study develops a cloud-based deep learning system for early prediction of diabetes, leveraging the distributed computing capabilities of the AW...
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...
Time synchronization is a critical component in network operation and management, and it is also required by Ultra-Reliable, Low-Latency Communicati...
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...
Early detection of drought stress is critical for taking timely measures for reducing crop loss before the drought impact becomes irreversible. The ...