These systems depend heavily on data annotation to train AI/ML models that enable real-time perception and decision-making. Raw data is collected from a suite of sensors, including LiDAR, radar, ...

"We are excited to launch the Object Detection and Classification solution, which significantly advances our SAR-based analytics for defense intelligence.

In conclusion, YOLOv8 is the most promising model for lung cancer object detection, tumor localization, and type classification, and it provides more accurate auxiliary diagnostics for medical image ...

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 ...

Deep neural networks (DNNs) play a crucial role in image classification and object detection, with applications in autonomous driving, security, Unmanned Aerial Vehicle (UAV) navigation, and robotics.

In this paper, we propose a classification committee for the active deep object detection method by introducing a discrepancy mechanism of multiple classifiers for samples' selection when training ...

Some frequent uses of object detection include self-driving automobiles, object tracking, face detection and identification, robotics, and license plate recognition. First, let’s have a peek at the ...