Accurate detection of these light sources is crucial for recognizing objects, predicting behaviors, and understanding the environment, particularly in the context of autonomous driving and surveillance systems.
On-Board AI refers to performing AI computations directly on the device, enabling real-time processing. Jetson, developed by NVIDIA, is a GPU-based platform ideal for high-performance tasks like robotics and autonomous driving. Hailo-8 is a low-power AI chip designed for fast inference in lightweight devices like CCTV and IoT sensors.
This video demonstrates how Data-Free Quantization works.
Data-Free Quantization is a model compression technique that reduces the precision of neural network weights and activations without requiring access to the original training data, typically by generating synthetic data or using statistical information to preserve model performance.
This video demonstrates how Multi-Modal Tracking works.
Multi-Modal Tracking is the process of simultaneously using and integrating information from multiple sensor modalities—such as RGB images, thermal cameras, depth sensors, or LiDAR—to robustly track objects over time, even in challenging environments.
3D Object Detection is a computer vision task that involves identifying, localizing, and estimating the size and orientation of objects in three-dimensional space using input data such as images, LiDAR point clouds, or RGB-D information.
The goal of multi-object tracking is to estimate the states of multiple objects, such as locations, velocities, and sizes, while conserving their identifications. We developed confidence-based tracking and online appearance learning, and deep learning algorithms to solve this problem.