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

The NAS algorithm can optimize the block separately and then find the best configuration of blocks in a large network. Search strategy Architecture of convolutional neural network (CNN) ...

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

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 ...

Figure 5. A generic convolutional neural network flow. ... This video is a good breakdown of the architecture in plain English. Transformers are very powerful, and also very complex.

Convolutional Neural Networks. Convolutional neural networks (CNNs) are a type of neural network that is designed to capture increasingly more complex features within its input data.To do this ...

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...