CORTEXA
← Browse
crossrefElectronics2024-01-30Cited by 1

Guest Editorial: Foreword to the Special Issue on Advanced Research and Applications of Deep Learning and Neural Network in Image Recognition

Ganggang Dong, Yuanxin Ye, Zhongling Huang

Over the last two decades, the realm of image recognition has undergone a remarkable transformation, characterized by an astonishing pace of advancement [...]

View free PDFSource page

Related papers

crossrefElectronics2024-11-21Cited by 9

Combination of a Rabbit Optimization Algorithm and a Deep-Learning-Based Convolutional Neural Network–Long Short-Term Memory–Attention Model for Arc Sag Prediction of Transmission Lines

Xiu Ji, Chengxiang Lu, Beimin Xie, Haiyang Guo, Boyang Zheng

Arc droop presents significant challenges in power system management due to its inherent complexity and dynamic nature. To address these challenges in predicting arc sag for transmission lines, this paper proposes an innovative time–series prediction model, AROA-CNN-LSTM-Attentio…

View free PDFSource page
crossrefElectronics2025-04-16Cited by 2

Batchnorm-Free Binarized Deep Spiking Neural Network for a Lightweight Machine Learning Model

Hasna Nur Karimah, Chankyu Lee, Yeongkyo Seo

The development of deep neural networks, although demonstrating astounding capabilities, leads to more complex models, high energy consumption, and expensive hardware costs. While network quantization is a widely used method to address this problem, the typical binary neural netw…

View free PDFSource page
crossrefElectronics2023-10-17Cited by 1

Deep Learning Neural Network-Based Detection of Wafer Marking Character Recognition in Complex Backgrounds

Yufan Zhao, Jun Xie, Peiyu He

Wafer characters are used to record the transfer of important information in industrial production and inspection. Wafer character recognition is usually used in the traditional template matching method. However, the accuracy and robustness of the template matching method for det…

View free PDFSource page
crossrefElectronics2024-11-06Cited by 14

Machine Learning and Deep Learning Applications in Disinformation Detection: A Bibliometric Assessment

Andra Sandu, Liviu-Adrian Cotfas, Camelia Delcea, Corina Ioanăș, Margareta-Stela Florescu, Mihai Orzan

Fake news is one of the biggest challenging issues in today’s technological world and has a huge impact on the population’s decision-making and way of thinking. Disinformation can be classified as a subdivision of fake news, the main purpose of which is to manipulate and generate…

View free PDFSource page
crossrefElectronics2023-02-06Cited by 7

Machine Design Automation Model for Metal Production Defect Recognition with Deep Graph Convolutional Neural Network

Yavuz Selim Balcıoğlu, Bülent Sezen, Ceren Cubukcu Çerasi, Shao Ho Huang

Error detection has a vital function in the production stages. Computer-aided error detection applications bring significant technological innovation to the production process to control the quality of products. As a result, the control of product quality has reached an essential…

View free PDFSource page