Researchers at Soongsil University (Korea) published “A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration.” Abstract: “Over the past decade, deep-learning-based ...

They are developing a Quantum Convolutional Neural Network (QCNN) architecture to enhance the performance of traditional computer vision tasks using quantum mechanics principles.

Fully convolutional networks (FCNs) are a type of neural network architecture commonly used in computer vision tasks such as image segmentation, object detection and image classification.

In this article, we delve into the fundamentals of Convolutional Neural Networks, their architecture, and their impact on the world of computer vision.

Convolutional neural networks One of the key components of most deep learning–based computer vision applications is the convolutional neural network (CNN).

A hardware accelerator unit for performing inference of convolutional neural networks is a distinct feature of the MAX7800x series of microcontrollers, which sets it apart from the standard ...

Description Convolutional Neural Networks (CNN) are mainly used for image recognition. The fact that the input is assumed to be an image enables an architecture to be created such that certain ...

Japanese carrier SoftBank has developed a new AI architecture using a Transformer model for radio access networks (RAN), the ...