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 networks need to be ...

Object detection is a supervised machine learning problem, which means you must train your models on labeled examples. Each image in the training dataset must be accompanied with a file that ...

A new machine learning technique developed by researchers at Edge Impulse, a platform for creating ML models for the edge, makes it possible to run real-time object detection on devices with very ...

These systems reliably detect objects under an array of conditions ... and documenting vulnerabilities in deep- and other machine-learning algorithms. Using SwRI internal research funds, Garza ...

Supported by the hyper scale of the Amazon Web Services (AWS) cloud, this robust dataset enables the patented SpotlightAI™ ecosystem to rapidly detect ... advanced machine learning (ML) models ...

The object detection required for machine vision applications such ... Thomas Andersen, vice president for AI and machine learning at Synopsys, said that in this situation, it depends on the actual ...

Might satellites bolstered with machine learning be up for the oceanic ... These differences in light absorption allow satellites to detect floating objects from space. The NIR signals of various ...