Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

Remote sensing object detection is a rapidly growing field in artificial intelligence, playing a critical role in advancing the use of unmanned aerial vehicles (UAVs) for real-world applications such ...

DEIMv2 is an evolution of the DEIM framework while leveraging the rich features from DINOv3. Our method is designed with various model sizes, from an ultra-light version up to S, M, L, and X, to be ...

Abstract: Source-Free Object Detection (SFOD) enables knowledge transfer from a source domain to an unsupervised target domain for object detection without access to source data. Most existing SFOD ...

The experimental objects and the conditions of the grasping task. Researchers at HSE University have developed a new methodological approach to studying motor planning and execution. By using ...

Physicists are exploring a quantum-mechanical approach to making smaller radio wave detectors. Physicists have created a new type of radar that could help improve underground imaging, using a cloud of ...

Abstract: Video object detection is essential for human-interaction applications, including bimanual manipulation sensing (BMS). The effects of video detection in practical applications still need to ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

According to a statement emailed to The Debrief and a separate story on the organization’s website, when Dr. John Sandusky first joined Sandia almost 20 years ago, he was asked if the heliostats at ...

Introduction: Accurate vehicle analysis from aerial imagery has become increasingly vital for emerging technologies and public service applications such as intelligent traffic management, urban ...