Learn how to measure and improve your artificial neural network (ANN) model performance and quality for object detection with data, metrics, and methods. Sign in to view more content ...

In this paper, an energy-efficient FPGA accelerator design of the SNN is proposed for object detection. This work concentrates on both algorithm optimization and hardware architecture design. In ...

This changed with the rise of powerful deep networks. Nowadays, tracking is dominated by pipelines that perform object detection followed by temporal association, also known as tracking-by-detection.

Aiming at the challenges of low detection accuracy, susceptibility to complex background interference, difficulty in detecting small objects, and multi-scale object issues in aerial images, our ...

Like all of Orbital Insight’s products, multiclass object detection was developed within an ethics framework that shapes the company’s work and values privacy. To learn more about Orbital ...

ANN model accuracy and robustness for object detection can be assessed using precision, recall, F1-score, mean average precision, intersection over union (IoU), and average IoU.