Latest AI and machine learning research in work force for healthcare professionals.
This paper analyzes the scientific production on the COVID-19 effect in the area of Information Sciences from a bibliometric perspective. The objectives focused on: 1) determining the most productive authors, countries, institutions and journals; 2) identifying the sources that constitute the core of scientific production; 3) examining the manuscripts with the greatest impact; and 4) visualizing...
The Fourth Industrial Revolution (4IR) technologies, such as cloud computing, machine learning, and AI, have improved productivity but introduced challenges in workforce training and reskilling. This is critical given existing workforce shortages, especially in marginalized communities like Underrepresented Minorities (URM), who often lack access to quality education. Addressing these challenges...
In the era of Large Language Models (LLMs), embodied artificial intelligence presents transformative opportunities for robotic manipulation tasks. U...
Large language models (LLMs) require immense resources for training and inference. Quantization, a technique that reduces the precision of model par...
Language is far more than a communication tool. A wealth of information - including but not limited to the identities, psychological states, and soc...
The co-design of robot morphology and neural control typically requires using reinforcement learning to approximate a unique control policy gradient...
This paper addresses the critical issue of burnout among cybersecurity professionals, a growing concern that threatens the effectiveness of digital ...
Image Captioning for state-of-the-art VLMs has significantly improved over time; however, this comes at the cost of increased computational complexi...
Multimodal visual language models are gaining prominence in open-world applications, driven by advancements in model architectures, training techniq...
Recent advancements in reinforcement learning (RL) have achieved great success in fine-tuning diffusion-based generative models. However, fine-tunin...
Can we derive computational metrics to quantify visual creativity in drawings across intelligent agents, while accounting for inherent differences i...
The generation of incorrect images, such as depictions of people of color in Nazi-era uniforms by Gemini, frustrated users and harmed Google's reput...
While diffusion models are powerful in generating high-quality, diverse synthetic data for object-centric tasks, existing methods struggle with scen...
Current Vision Language Models (VLMs) remain vulnerable to malicious prompts that induce harmful outputs. Existing safety benchmarks for VLMs primar...
Image generation abilities of text-to-image diffusion models have significantly advanced, yielding highly photo-realistic images from descriptive te...
Single-domain generalization for object detection (S-DGOD) aims to transfer knowledge from a single source domain to unseen target domains. In recen...
The widespread use of chest X-rays (CXRs), coupled with a shortage of radiologists, has driven growing interest in automated CXR analysis and AI-ass...
This study presents a novel framework for precise force control of fin-actuated underwater robots by integrating a deep neural network (DNN)-based s...
Outfit generation is a challenging task in the field of fashion technology, in which the aim is to create a collocated set of fashion items that com...
BACKGROUND: High-stress environments, heavy workloads, and the emotional demands of patient care, which are common challenges faced by nurses, are fac...