Understanding the different forms and future directions of Artificial Intelligence (AI) is becoming increasingly important as it evolves. Artificial Narrow Intelligence (ANI), Artificial General ...

In the rapidly evolving field of artificial intelligence, the focus often lies on large, complex models requiring immense computational resources. However, many practical use cases call for smaller, ...

The quest to strengthen national security has faced several challenges over the years, especially as the pace of technological advancement has far outstripped the speed of legislative and bureaucratic ...

A fundamental challenge in studying EEG-to-Text models is ensuring that the models learn from EEG inputs and not just memorize text patterns. In many reports in the literature where great results have ...

Tracking dense 3D motion from monocular videos remains challenging, particularly when aiming for pixel-level precision over long sequences. Existing methods face challenges in achieving detailed 3D ...

Automatic differentiation has transformed the development of machine learning models by eliminating complex, application-dependent gradient derivations. This transformation helps to calculate Jacobian ...

Information overload presents significant challenges in extracting insights from documents containing both text and visuals, such as charts, graphs, and images. Despite advancements in language models ...

The advent of AI has revolutionized the landscape of graphic design. AI graphic design tools are reshaping the way designers work, offering unprecedented efficiency, creativity, and innovation. These ...

Ischemic stroke (IS) is one of the leading causes of disability and mortality in the world. It is caused by blood clotting in the arteries leading to the brain. It is crucial to dissolve the clot ...

Recognition of human motion using time series from mobile and wearable devices is commonly used as key context information for various applications, from health condition monitoring to sports activity ...

Atmospheric science and meteorology have recently made strides in modeling local weather and climate phenomena by capturing fine-scale dynamics crucial to precise forecasting and planning. Small-scale ...

Autonomous agents have emerged as a critical focus in machine learning research, especially in reinforcement learning (RL), as researchers work to develop systems that can handle diverse challenges ...