Real-time object detection, which uses neural networks and deep learning to rapidly identify and tag objects of interest in a video feed, is a handy feature with great hacker potential. Happily, it… ...

In this post, I will briefly review the deep learning architectures that help computers detect objects. Convolutional neural networks. One of the key components of most deep learning–based ...

As more convolutional and pooling layers are added, the feature maps zoom out and can detect complicated things such as faces and objects. Each layer of the neural network encodes specific ...

Convolutional neural networks (CNNs) are a class of deep neural networks commonly used in computer vision tasks such as image and video recognition, object detection and image segmentation.

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to ...

A Convolutional Neural Network (CNN) represents a sophisticated advancement in artificial intelligence technology, specifically designed to process and analyze visual information.

A Convolutional Neural Network (CNN) is a form of artificial intelligence that plays a key role in the AI ecosytem due to its ability to analyze and understand visual data. The need to decipher ...

The rise of real-time object detection and CNN models like YOLO is powering operational efficiency across ports, warehouses, ...