Feb 21, 2023 Chiral detection of biomolecules based on reinforcement learning (Nanowerk News) As one of basic physical properties, chirality plays an important role in many fields. Especially in ...

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 ...

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 ...

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.

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 ...

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 ...

But another kind of AI — deep reinforcement learning — is strategic. It learns how to take a series of actions in order to reach a goal.

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 ...

Engineers develop novel techniques to trick object detection systems Project to test and improve deep-learning algorithms for enhanced security Date: April 4, 2019 Source: Southwest Research ...