Future integration of the deep learning algorithm into standard system software would allow factory engineers to train networks that could then be run locally for inspection. There are many more ...

But most machine learning researchers and developers use one of several tried and tested convolutional neural networks such as AlexNet, VGG16, and ResNet-50. Object detection datasets ...

Deep tech Here’s how deep learning helps computers detect objects From autonomous driving to healthcare, object detection is used for many things June 28, 2021 - 2:27 pm ...

Redefining object detection deep learning architectures FOMO also applies a major structural change to traditional deep learning architectures. Single-shot object detectors are composed of a set ...

A Smart IoT Enabled End-to-End 3D Object Detection System for Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems, 2022; 1 DOI: 10.1109/TITS.2022.3210490 ...

Researchers have designed an intelligent household robot capable of autonomous navigation, object detection, and sorting.

This new technical paper titled “End-to-end deep learning framework for printed circuit board manufacturing defect classification” is from researchers at École de technologie supérieure (ÉTS) in ...

TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, saving time and resources.

Real-time object detection, which uses neural networks and deep learning to rapidly identify and tag objects of interest in a video feed, is a handy feature with great hacker potential. Happily, it… ...

The AttendSeg deep learning model performs semantic segmentation at an accuracy that is almost on-par with RefineNet while cutting down the number of parameters to 1.19 million.