'Understanding human activity in images and/or videos is a fundamental step toward building socially aware agents, semantic image/video retrieval, captioning, and question-answering,' Huang said.

Image classification vs object detection. TinyML has made great progress in image classification, where the machine learning model must only predict the presence of a certain type of object in an ...

Fig. 1: DETR transformer model compares its prediction with the ground truth. When there is no match, it would yield a “no object.” A match would validate an object. Source: “End-to-End Object ...

Object classification, detection, and segmentation One of the key reasons for the growing interest in machine learning systems is the problems they can solve in computer vision .

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 ...

In a study published in the journal Information Systems Research, Texas Tech University's Shuo Yu and his collaborators ...

It comes with Azure Machine Learning, a cloud service to build and deploy ML models faster. In the monthly September update to ML.NET -- bringing it to v1.5.2 -- Microsoft introduced: The ability to ...

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior ...

“Successful machine learning is only as good as the data available, which is why it needs new, updated data to provide the most accurate outputs or predictions for any given need,” said ...