Results 71 to 80 of about 849,090 (345)

Despeckling of SAR Images Using Residual Twin CNN and Multi-Resolution Attention Mechanism

Remote Sensing, 2023
The despeckling of synthetic aperture radar images using two different convolutional neural network architectures is presented in this paper. The first method presents a novel Siamese convolutional neural network with a dilated convolutional network in ...
Blaž Pongrac, Dušan Gleich
doaj   +1 more source

Dependency-based Convolutional Neural Networks for Sentence Embedding

, 2015
In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies. To exploit both deep learning
Huang, Liang, Ma, Mingbo, Xiang, Bing, Zhou, Bowen   +3 more
core   +1 more source

Structurally Colored Physically Unclonable Functions with Ultra‐Rich and Stable Encoding Capacity

Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.
This study reports a design strategy for generating bright‐field resolvable physically unclonable functions with extremely rich encoding capacity coupled with outstanding thermal and chemical stability. The optical response emerges from thickness‐dependent structural color formation in ZnO features, which are fabricated by physical vapor deposition ...
Abidin Esidir, Miaoning Ren, Sami Pekdemir, Mustafa Kalay, Nilgun Kayaci, Nail Gunaltay, Hakan Usta, Xian Huang, Mustafa Serdar Onses   +8 more
wiley   +1 more source

Research on Fault Diagnosis of HMCVT Shift Hydraulic System Based on Optimized BPNN and CNN

Agriculture, 2023
There are some problems in the shifting process of hydraulic CVT, such as irregularity, low stability and high failure rate. In this paper, the BP neural network and convolutional neural network are used for fault diagnosis of the HMCVT hydraulic system.
Jiabo Wang, Zhixiong Lu, Guangming Wang, Ghulam Hussain, Shanhu Zhao, Haijun Zhang, Maohua Xiao   +6 more
doaj   +1 more source

Carbon Nanotube 3D Integrated Circuits: From Design to Applications

Advanced Functional Materials, EarlyView.
As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu, Yun Sun, Dong‐Ming Sun, Hui‐Ming Cheng   +3 more
wiley   +1 more source

Convolutional Neural Network Language Models [PDF]

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016
Convolutional Neural Networks (CNNs) have shown to yield very strong results in several Computer Vision tasks. Their application to language has received much less attention, and it has mainly focused on static classification tasks, such as sentence classification for Sentiment Analysis or relation extraction.
Pham, Ngoc-Quan, Kruszewski, Germán, Boleda, Gemma   +2 more
openaire   +3 more sources

Temperature‐Resilient Polymeric Memristors for Effective Deblurring in Static and Dynamic Imaging

Advanced Functional Materials, EarlyView.
A thermally stable organic memristor based on a thiadiazolobenzotriazole (TBZ) and 2,5‐Dioctyl‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4(2H,5H)‐dione (DPP)‐based conjugated polymer is presented, demonstrating reliable, gradual resistance switching across a wide temperature range (153–573 K).
Ziyu Lv, Ming‐Hao Jiang, Hui‐Ying Liu, Qing‐Xiu Li, Tao Xie, Jingya Yang, Yan Wang, Yongbiao Zhai, Guanglong Ding, Shirui Zhu, Jia‐Hua Li, Miao Zhang, Ye Zhou, Bobo Tian, Wai‐Yeung Wong, Su‐Ting Han   +15 more
wiley   +1 more source

FocusedDropout for Convolutional Neural Network

Applied Sciences, 2022
In a convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially. Except for randomly discarding regions or channels, many approaches try to overcome this defect by dropping influential units.
Minghui Liu, Tianshu Xie, Xuan Cheng, Jiali Deng, Meiyi Yang, Xiaomin Wang, Ming Liu   +6 more
openaire   +2 more sources

Performance of a Convolutional Neural Network-Based Artificial Intelligence Algorithm for Automatic Cephalometric Landmark Detection

Turkish Journal of Orthodontics, 2022
Objective: The aim of this study is to develop an artificial intelligence model to detect cephalometric landmark automatically enabling the automatic analysis of cephalometric radiographs which have a very important place in dental practice and is used ...
Mehmet Uğurlu
doaj   +1 more source

Learning to Detect Violent Videos using Convolutional Long Short-Term Memory

, 2017
Developing a technique for the automatic analysis of surveillance videos in order to identify the presence of violence is of broad interest. In this work, we propose a deep neural network for the purpose of recognizing violent videos.
Lanz, Oswald, Sudhakaran, Swathikiran
core   +1 more source