Sensor and Data Collection ADAS/AD relies heavily on perception sensors like cameras, radars, LiDARs, ultrasonics, and, more ...

In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and ...

Delivery robots made by companies such as Starship Technologies and Kiwibot autonomously make their way along city streets ...

Purdue engineers are developing CT-Bound and MetaHDR, imaging technologies with applications as broad as medical imaging, ...

A collaborative research effort between UNIST and the Korea Institute of Science and Technology (KIST) has led to the ...

Research students at LSU are working to decrease intersection crashes through implementing an artificial intelligence algorithm that can quickly detect and react to traffic lights.

Researchers at Rice University have developed a new machine learning (ML) algorithm that excels at interpreting the "light ...

In contrast, the study revealed that when the model analyzes non-academic writing, its accuracy is 53%. Workado, however, deceptively used the 98% accuracy data point to advertise its non-academic AI ...

A machine learning model using treated astigmatism and other nuanced inputs can significantly improve the accuracy and personalization of arcuate keratotomy planning ...

The team who originally created syslog‑ng™ now delivers on its promise: you don't have to write configs to consume detection‑ready data. Reduction—that also comes out‑of‑the‑box ...

SAN FRANCISCO, April 29, 2025--(BUSINESS WIRE)--ExtraHop, a leader in modern network detection and response (NDR), today launched the industry’s first all-in-one sensor designed to unify network ...

This study evaluates several object detection algorithms under low illumination conditions, comparing traditional methods including SIFT, SURF, ORB, BRISK, KAZE, and AKAZE with the deep learning model ...