Object detection models are much more complex than image classification networks and require more memory. “We added computer vision support to Edge Impulse back in 2020, and we’ve seen a ...

Real-time object detection, which uses neural networks and deep learning to rapidly identify and tag objects of interest in a video feed, is a handy feature with great hacker potential. Happily, it… ...

However, considering the small network size, adding object detection classes will increase the size and memory consumption of the network, thus object detection with up to 3 classes is demonstrated.

Ritsumeikan University researchers introduce DPPFA−Net, a groundbreaking 3D object detection network melding LiDAR and image data to improve accuracy for robots and self-driving cars. Addressing ...

The novel SBDet model introduces a relaxed rotation-equivariant network (R2Net) that improves object detection in scenarios with symmetry-breaking or non-rigid transformations. This innovation ...