The study identifies persistent challenges that limit the adoption and scalability of AI- and IoT-enabled assistive systems.

Abstract: This study develops a scalable, effective, and user-friendly solution to tackle the problem of real-time object detection in photos. The suggested approach ...

From Human Judgment to Algorithmic Intelligence Traditional driving relies on human perception, reaction time, and experience ...

Humans can detect buried objects without touching them, sensing faint pressure ripples in sand. Scientists are calling this ...

Testing demonstrates 48% file size reduction with robust ML model accuracy across multiple industry-standard metrics. AV teams are invited to ...

Future Market Insights, Inc. (FMI) is an ESOMAR-certified, ISO 9001:2015 market research and consulting organization, trusted by Fortune 500 clients and global enterprises. With operations in the U.S.

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

BONUS: Custom Object Counting Mode (TensorFlow implementation): You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to ...

This repository is the official Pytorch implementation for the paper Rethinking Multi-modal Object Detection from the Perspective of Mono-Modality Feature Learning. If you have any questions, please ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...