Miniaturized electronics and intricate objects require a certain finesse. Researchers have looked into the development of a ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...

The most sophisticated machine vision systems have enabled new and emerging designs far more sophisticated than bin picking.

A new study applying multi-omics techniques and machine learning identified 33 plasma proteins that differ significantly in patients with amyotrophic lateral sclerosis (ALS). The findings suggest ALS ...

A new trick for modeling molecules with quantum accuracy takes a step toward revealing the equation at the center of a popular simulation approach, which is used in fundamental chemistry and materials ...

Abstract: Detection, classification and identification of underwater objects are both complex and essential tasks for perception and navigation of Autonomous Underwater Vehicles (AUVs) and Remotely ...

I tried using DINOv3 as the pre-trained model for the detector and encountered an issue. When defining the Transformer, self.reference_points（not two-stage） is initialized as follows: if two_stage: ...

Abstract: Object recognition and grasping position detection are critical tasks in robotic manipulation, particularly when operating in dynamic and unstructured environments. This paper presents the ...

ABSTRACT: 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 ...