Based on the deep learning method, the convolutional neural network model is used to extract ... the plane and angle of a 3D object associated with different directions and positions. In addition, CNN ...

A new study questions the longstanding view that the visual system is divided into two pathways, one for object-recognition and the other for spatial tasks. Using computational vision models, ...

Roboflow has launched RF-DETR, a real-time object detection model tailored for embedded systems ... split large images—like charts, tables, or diagrams—into tiles for more efficient feature ...

This paper presents a depression detection network (DDNet), a novel approach utilizing a three-stage stacked ensemble model to address this challenge. The proposed model incorporates two different ...

Compromising the attack detection model itself can result in the breakdown of normal attack detection capabilities. Ensuring the security of the attack detection model during runtime presents a novel ...

RF-DETR is a real-time, transformer-based object detection model architecture developed by Roboflow and released under the Apache 2.0 license. RF-DETR is the first real-time model to exceed 60 AP on ...

In summary, vehicle detection involves using a deep learning model to identify vehicles in video frames, tracking their movements, calculating attributes like speed and direction, and providing this ...