New adversarial techniques developed by engineers can make objects 'invisible' to image detection systems that use deep-learning algorithms. These techniques can also trick systems into thinking ...

In fact, most object detection networks use an image classification CNN and repurpose it for object detection. Object detection is a supervised machine learning problem, which means you must train ...

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 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 ...

Arm Ltd., the U.K. chip intellectual property vendor, is rolling out a machine learning platform designed to boost the functionality of devices at the network edge, beginning with an object detection ...

Six members of Facebook AI Research (FAIR) tapped the popular Transformer neural network architecture to create end-to-end object detection AI, an approach they claim streamlines the creation of ...

A match would validate an object. Source: “End-to-End Object Detection with Transformers,” Facebook AI. Most object detection models make initial predictions, then fine-tune them to produce the final ...

Bolstering the safety of self-driving cars with a deep learning-based object detection system. ScienceDaily. Retrieved May 13, 2025 from www.sciencedaily.com / releases / 2022 / 12 / 221212140800.htm.

In brief: Thanks to machine learning, object detection has come a long way in recent years, but most models still perform best on low-resolution video images. Now, researchers at Carnegie Mellon ...