TMCnet

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Three-Dimensional Object Technology for Multi-Channel Quantum Convolutional Neural Networks

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a forward-looking technological achievement: the hybrid quantum-classical three-dimensional ...

New holographic storage method uses light to pack more data in less space

Light has always carried more than brightness. In this case, it also carries direction and twist. That mix may open a new ...
AZoRobotics

Detecting IoT Malware in EV Chargers with Deep Learning

A new study presents a deep learning approach for IoT malware detection in EV charging stations, addressing key limitations ...
Scientific Research Publishing

Yan, Y., Mao, Y. and Li, B. (2018) SECOND: Sparsely Embedded Convolutional Detection. Sensors, 18, Article No. 3337.

ABSTRACT: Point cloud-based 3D object detection is a key technology in autonomous driving and mobile robot perception systems. However, the sparsity and irregularity of point cloud data result in poor ...
IEEE

Supervised Convolutional Encoder-Decoder With Gated Linear Units for Detecting Fetal R-Peaks

Abstract: Noninvasive fetal electrocardiography (ECG) is prevalently used for monitoring fetal heartbeats during pregnancy due to its affordability, ease of use, and constant monitoring capability. A ...
EurekAlert!

Quasi-convolution coding empowers streamlined reservoir computer

A new publication from Opto-Electronic Sciences; DOI 10.29026/oea.2025.240135, discusses how quasi-convolution coding empowers a streamlined reservoir computer. As the pace of digitalization ...
Scientific Research Publishing

Chollampatt, S. and Ng, H.T. (2018) A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction. Proceedings of the AAAI Conference on Artificial ...

ABSTRACT: With the widespread use of Chinese globally, the number of Chinese learners has been increasing, leading to various grammatical errors among beginners. Additionally, as domestic efforts to ...
IEEE

Optimizing the Hyperparameters of Fully Convolutional Encoder–Decoder Networks for SAR Image Segmentation

Abstract: Fully convolutional encoder-decoder networks have been developed for the segmentation of sensing synthetic aperture radar (SAR) images. A recent one called the multiscaled attention U-net ...
marktechpost

Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural ...