Aeva sells 4D lidar-on-chip systems that combine sensing and processing on a single silicon chip. Its primary markets include automated driving, robotics, and consumer devices. The company is part of ...

Object detection is the task of identifying and localising instances of predefined object classes within images or video frames. Early approaches relied on handcrafted features and sliding-window ...

Fault detection involves identifying and diagnosing issues in machines or equipment to prevent failures and ensure optimal performance. Computer vision plays a role in engineering fault detection by ...

The Narwal Flow 2 holds its own against pricier 2026 Dreame and Roborock competitors. It's the only mainstream roller mop vacuum that mops with heated water, and its AI cameras provide reliable ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

For decades, the retail industry has faced the same persistent problems of empty shelves, pricing errors and inventory discrepancies. Despite having spent billions of dollars on data analytics and ...

California-based Cognixion is launching a clinical trial to allow paralyzed patients with speech disorders the ability to communicate without an invasive brain implant. Cognixion is one of several ...

The rapid deployment of solar photovoltaic (PV) systems has created a growing challenge in managing end-of-life panels. While many studies project future recycling potential, they are often limited by ...

The race between deepfake creators and detectors has entered a new phase, with researchers from the Netherlands revealing tech that reads the human heartbeat through video analysis. While artificial ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...