Results 41 to 50 of about 278,943 (296)

Deep learning in distributed denial-of-service attacks detection method for Internet of Things networks

Journal of Intelligent Systems, 2023
With the rapid growth of informatics systems’ technology in this modern age, the Internet of Things (IoT) has become more valuable and vital to everyday life in many ways. IoT applications are now more popular than they used to be due to the availability
Aswad Firas Mohammed, Ahmed Ali Mohammed Saleh, Alhammadi Nafea Ali Majeed, Khalaf Bashar Ahmad, Mostafa Salama A.   +4 more
doaj   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

A Review Study on Investing Deep Learning in The Field of Virtual Dressing

Syrian Journal for Science and Innovation
This study provides a comprehensive review and detailed analysis of existing works based on deep learning for 3D pose estimation, transforming 2D clothing items into a person’s image using artificial intelligence (AI) techniques to develop virtual ...
Sarah SHIKH ALSHABAB, Chadi Albitar
doaj   +1 more source

Noise‐Limited Bit Precision in Ferroelectric Synaptic Transistors for High‐Resolution Neuromorphic Computing

Advanced Functional Materials, EarlyView.
Low‐frequency noise spectroscopy defines the resolvable conductance states of synaptic FeFETs by coupling read‐current fluctuation with usable dynamic range. The resulting noise‐limited bit precision establishes a universal, device‐agnostic reliability metric beyond the memory window, enabling quantitative benchmarking and rational design of high ...
Jaehong Park, Yeonseop Shin, Changhyeon Han, Sangwoo Kim, Eunchan Park, Youngchan Cho, Jaehong Min, Hyunjun Ahn, Jaekyoung Park, Cheol‐Woong Yang, Jangsaeng Kim, Daewoong Kwon, Wonjun Shin   +12 more
wiley   +1 more source

P-CNN: Percept-CNN for semantic segmentation

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
The task of image segmentation remains a fundamental challenge, in the field of computer vision. Convolutional Neural Networks (CNNs) have achieved significant success in this field, yet there are some limitations in the conventional approach. The process of accurate, pixel-wise image annotation is time-consuming, as well as requires more human effort.
Deepak Hegde, G. N. Balaji
openaire   +3 more sources

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 more
wiley   +1 more source

Estimation of Hourly Rainfall during Typhoons Using Radar Mosaic-Based Convolutional Neural Networks

Remote Sensing, 2020
Taiwan is located at the junction of the tropical and subtropical climate zones adjacent to the Eurasian continent and Pacific Ocean. The island frequently experiences typhoons that engender severe natural disasters and damage.
Chih-Chiang Wei, Po-Yu Hsieh
doaj   +1 more source

Generalized CNN: Potentials of a CNN with non-uniform weights [PDF]

CNNA '92 Proceedings Second International Workshop on Cellular Neural Networks and Their Applications, 2003
A generalization of the cellular neural network (CNN) paradigm is obtained by removing the uniformly constraint on weight values. Such generalized CNNs are capable of new tasks, such as function approximation or associative memory. A stability analysis of these networks is presented.
openaire   +2 more sources

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source