IEEE

An Attention-Based Convolutional Neural Network With Spatial Transformer Module for Automated Optical Inspection of Small Objects

Abstract: In the manufacturing industry, automated optical inspection (AOI) systems play a crucial role in accurate and efficient inspection. Recently, convolutional neural networks (CNNs) have become ...
Frontiers

Efficient spiking convolutional neural networks accelerator with multi-structure compatibility

1 College of Electronic Science and Technology, National University of Defense Technology, Changsha, China 2 College of Electronics and Internet of Things, Chongqing Polytechnic University of ...
Frontiers

TFANet: a temporal fusion attention neural network for motor imagery decoding

Introduction: In the field of brain-computer interfaces (BCI), motor imagery (MI) classification is a critically important task, with the primary objective of decoding an individual's MI intentions ...
Scientific Research Publishing

Prediction of Building Displacements during Wind Gusts Using Support Vector Regression and Deep Neural Network ()

The significance of artificial intelligence in contemporary human activities cannot be underestimated. Although the application of this technology in structural engineering is not recent, advancements ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
GitHub

Convolutional Logic Networks Code and RTL implementation

Hi, First of all great work. Wanted to know if the code for convolution LGN is going to be publicly available anytime soon? Also, I was quite curious about the adder tree structure that mimics ...
IEEE

Surrogate-Assisted Evolution of Convolutional Neural Networks by Collaboratively Optimizing the Basic Blocks and Topologies

Abstract: Convolutional neural networks (CNNs) are prominent in many fields owing to their outstanding feature extraction abilities. Many excellent CNNs have been carefully designed by algorithm ...
Microsoft

Learning from Source Code

Over the last five years, deep learning-based methods have revolutionised a wide range of applications, for example those requiring understanding of pictures (opens in new tab), speech and natural ...