Science Daily

Scientists adopt deep learning for multi-object tracking

Researchers have adapted deep learning techniques in a multi-object tracking framework, overcoming short-term occlusion and achieving remarkable performance without sacrificing computational speed.
The Debrief

DARPA Launches TBD2, the First Deep-Space Surveillance Network to Track Tiny Objects Millions of Miles From Earth

DARPA’s TBD2 program aims to track tiny spacecraft across deep space, creating the first wide-area surveillance of the ...
InfoQ

Unsupervised Object Detection and Semantic Segmentation Using Deep Learning

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
The Next Web

Here’s how deep learning helps computers detect objects

Deep neural networks have gained fame for their capability to process visual information. And in the past few years, they have become a key component of many computer vision applications. Among the ...
Scientific Research Publishing

Covariant-Scale: Riemannian Manifold Learning for Scale-Invariant Video Anomaly Detection ()

Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera images ...