Suchergebnisse - convolutional autoen-coder~

Objective Image Quality Analysis of Convolutional Neural Network Light Field Coding

Autoren: Medda D. Song W. Perra C.

Quelle: 2019 8th European Workshop on Visual Information Processing (EUVIP). :163-168

Schlagwörter: autoen-coder, coding, compression, convolutional neural network, image quality, light field, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://dblp.uni-trier.de/db/conf/euvip/euvip2019.html#Medda0P19
https://hdl.handle.net/11584/284536
https://doi.org/10.1109/EUVIP47703.2019.8946230
https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8596718

基于复值卷积降噪自编码器去噪的矢量水听器 DOA估计方法. (Chinese)

Alternate Title: Vector Hydrophone DOA Estimation Method Based on Complex Valued Convolutional Denoising Autoencoder Denoising. (English)

Autoren: 任晶 谭秀辉 白艳萍 et al.

Quelle: Journal of Test & Measurement Technology; 2025, Vol. 39 Issue 4, p475-490, 9p

Improving Image Reconstruction using Incremental PCA-Embedded Convolutional Variational Auto-Encoder

Autoren: Azizi, Amir Charambous, Panayiotis Chrysanthou, Yiorgos et al.

Weitere Verfasser: Azizi, Amir Charambous, Panayiotis Chrysanthou, Yiorgos et al.

Schlagwörter: zpracování obrazu, rekonstrukce obrazu, analýza hlavních komponent, konvoluční variační automatické kodéry, image processing, image reconstruction, principal component analysis, Convolutional Variational Auto-encoders

Dateibeschreibung: 10 s.; application/pdf

Relation: 2464–4625 (online); 2464–4617 (print); http://hdl.handle.net/11025/57383; https://doi.org/10.24132/10.24132/CSRN.3401.12

Verfügbarkeit: http://hdl.handle.net/11025/57383
https://doi.org/10.24132/10.24132/CSRN.3401.12

Generating Synthetic Short-Range FMCW Range-Doppler Maps Using Generative Adversarial Networks and Deep Convolutional Autoencoders

Autoren: Marcio L. Lima de Oliveira Marco J. G. Bekooij

Quelle: 2020 IEEE Radar Conference (RadarConf20). :1-6

Schlagwörter: Synthetic Data, Generative Adversarial Networks, Deep Learning, Radar, FMCW, Neural Network, 22/2 OA procedure, 0202 electrical engineering, electronic engineering, information engineering, Autoencoder, Convolutional, 02 engineering and technology, Doppler-Range

Zugangs-URL: https://research.utwente.nl/en/publications/c94aacd6-24c4-40e1-b4f2-ba95ec0b9508
https://doi.org/10.1109/RadarConf2043947.2020.9266348
https://utwente-staging.elsevierpure.com/en/publications/generating-synthetic-short-range-fmcw-range-doppler-maps-using-ge
https://research.utwente.nl/en/publications/generating-synthetic-short-range-fmcw-range-doppler-maps-using-ge
https://www.narcis.nl/publication/RecordID/oai%3Aris.utwente.nl%3Apublications%2Fc94aacd6-24c4-40e1-b4f2-ba95ec0b9508

结合深度学习和迁移学习的行星齿轮箱故障诊断算法研究. (Chinese)

Alternate Title: Research on Planetary Gearbox Fault Diagnosis Algorithm Combining Deep Learning and Transfer Learning. (English)

Autoren: 陈超 许琦 宋正华 et al.

Quelle: Machine Tool & Hydraulics; May2025, Vol. 53 Issue 10, p40-49, 10p

Schlagwörter: CONVOLUTIONAL neural networks, LONG short-term memory, FAULT diagnosis, TRANSFER of training, GEARBOXES, SAMPLE size (Statistics)

Prediction of Residual Life of Rolling Bearings Based on Multi-Scale Improved Temporal Convolutional Network (MITCN) Model.

Autoren: Xia, Keru Li, Qi Han, Luyuan et al.

Quelle: Machines; Feb2025, Vol. 13 Issue 2, p137, 14p

Schlagwörter: TIME series analysis, ROLLER bearings, PROBLEM solving, FORECASTING

基于时空差分图卷积神经网络的 古代石拱桥损伤识别研究. (Chinese)

Alternate Title: Research on damage detection of ancient stone arch bridges based on spatio-temporal difference graph convolutional neural network. (English)

Autoren: 张承文 淳庆 马宇坤 et al.

Quelle: Journal of Southeast University / Dongnan Daxue Xuebao; Mar2025, Vol. 55 Issue 2, p370-379, 10p

Noise-aware progressive multi-scale deepfake detection.

Autoren: Ding, Xinmiao Pang, Shuai Guo, Wen

Quelle: Multimedia Tools & Applications; Nov2024, Vol. 83 Issue 36, p83677-83693, 17p

Schlagwörter: CONVOLUTIONAL neural networks, FORGERY, DATA mining, TRUST, GLOBAL method of teaching, DIGITAL images

基于多模态集成卷积神经网络的数控机床齿轮箱故障诊断. (Chinese)

Alternate Title: Fault Diagnosis of Gearbox of CNC Machine Tool Based on Multimodal Ensemble Convolutional Neural Network. (English)

Autoren: 姜广君 杨永吉 王赜

Quelle: Machine Tool & Hydraulics; apr2024, Vol. 52 Issue 8, p202-207, 6p

Application of a Convolutional Autoencoder to Half Space Radar Hrrp Recognition

Autoren: Yong-Jun Xie Shi-Hao Yu

Quelle: 2018 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). :48-53

Schlagwörter: 2. Zero hunger, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Zugangs-URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8521306
https://ieeexplore.ieee.org/document/8521306/

Potato disease prediction using machine learning, image processing and IoT – a systematic literature survey.

Autoren: Gupta, Ayushi Chug, Anuradha Singh, Amit Prakash

Quelle: Journal of Crop Improvement; Mar2024, Vol. 38 Issue 2, p95-137, 43p

Schlagwörter: CONVOLUTIONAL neural networks, IMAGE processing, MACHINE learning, POTATOES, CITRUS greening disease, LEAF spots, BLIGHT diseases (Botany)

Multimodal Biometric Authentication System Using of Autoencoders and Siamese Networks for Enhanced Security

Autoren: Gueuret, Théo Kerkeni, Leila

Quelle: Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 23, Iss 1 (2024)

Schlagwörter: TK7885-7895, Computer engineering. Computer hardware, Deep Learning, Autoen-coder, Voice Recognition, Siamese Neural Network, User Authentication, Electronic computers. Computer science, QA75.5-76.95, Fusion, 16. Peace & justice, Face Recognition, Multimodal Biometrics

Dateibeschreibung: application/pdf

Zugangs-URL: https://doaj.org/article/e5dbf8c445984576af3f04796781532d
https://ddd.uab.cat/record/291506

A multimodal biometric authentication system using of autoencoders and Siamese networks for enhanced security

Autoren: Gueuret, Théo Kerkeni, Leila

Schlagwörter: User Authentication, Multimodal Biometrics, Deep Learning, Siamese Neural Network, Autoen-coder, Face Recognition, Voice Recognition, Fusion

Dateibeschreibung: application/pdf

Relation: ELCVIA. Electronic letters on computer vision and image analysis; Vol. 23 Núm. 1 (2024), p. 1-14; https://ddd.uab.cat/record/291506; urn:10.5565/rev/elcvia.1811; urn:oai:ddd.uab.cat:291506; urn:oai:elcvia.revistes.uab.cat:article/1811; urn:oai:raco.cat:article/980000001023

Verfügbarkeit: https://ddd.uab.cat/record/291506

Anomaly Detection in the CMS L1 Trigger.

Autoren: Quinnan, Melissa

Quelle: EPJ Web of Conferences; 10/7/2025, Vol. 337, p1-6, 6p

双约束深度卷积网络的高光谱图像空谱解混方法. (Chinese)

Alternate Title: Spectral-Spatial Hyperspectral Unmixing Using Deep Double-Constraints Convolutional Network. (English)

Autoren: 朱治青 苏远超 李朋飞 et al.

Quelle: Journal of Signal Processing; Jan2023, Vol. 39 Issue 1, p128-142, 15p

基于 TCN-GAT 与混合神经网络的汽车涂装 烘干系统能耗异常检测. (Chinese)

Alternate Title: Energy Consumption Anomaly Detection of Automobile Painting Drying System Based on TCN-GAT and Hybrid Neural Network. (English)

Autoren: 李聪波 翟贺旺 吴 畏 et al.

Quelle: China Mechanical Engineering; Aug2025, Vol. 36 Issue 8, p1864-1874, 11p

Schlagwörter: BACK propagation, ANOMALY detection (Computer security), PARETO distribution, AUTOMOBILE industry, ENERGY consumption

Comparative Evaluation of Autoencoders for Semi-Supervised Anomaly Detection on Univariate Time Series Data

Autoren: Markovic, Tijana Moricz, S. Leon, Miguel

Index Begriffe: Anomaly Detection, Autoencoders, Convolutional Neural Networks, Long-short Term Memory, Time Series, Computer and Information Sciences, Data- och informationsvetenskap, Conference paper, info:eu-repo/semantics/conferenceObject, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-70740
Proc. - Int. Conf. Mach. Learn. Appl., ICMLA, p. 1321-1328

Self-Supervised Learning of Satellite-Derived Vegetation Indices for Clustering and Visualization of Vegetation Types.

Autoren: Sharma, Ram C. Hara, Keitarou

Quelle: Journal of Imaging; Feb2021, Vol. 7 Issue 2, p1-13, 13p

Schlagwörter: PLANT classification, SUPERVISED learning, IMAGE compression, CONVOLUTIONAL neural networks, FEATURE extraction, DATA visualization

Machine learning applications in Alzheimer's disease research: a comprehensive analysis of data sources, methodologies, and insights.

Autoren: Rezaie, Zahra Banad, Yaser

Quelle: International Journal of Data Science & Analytics; Oct2025, Vol. 20 Issue 4, p3169-3203, 35p

SurfNet: Learning Surface Representations via Graph Convolutional Network.

Autoren: Han, Jun Wang, Chaoli

Quelle: Computer Graphics Forum; Jun2022, Vol. 41 Issue 3, p109-120, 12p, 8 Color Photographs, 7 Diagrams, 5 Charts, 1 Graph

Schlagwörter: REPRESENTATIONS of graphs, SCIENTIFIC visualization, DEEP learning, SPACE exploration