Výsledky vyhledávání - "Convolutional autoencoder"

Integrasi Convolutional Autoencoder dengan Support Vector Machine untuk Klasifikasi Varietas Almond

Autoři: Rizal Fadlullah Sri Winarno Muhammad Naufal

Zdroj: JuTISI (Jurnal Teknik Informatika dan Sistem Informasi), Vol 11, Iss 1, Pp 63-77 (2025)

Témata: Technology, machine learning, Electronic computers. Computer science, klasifikasi, support vector machine, QA75.5-76.95, varietas almond, convolutional autoencoder

Přístupová URL adresa: https://doaj.org/article/0b190ecfac37461bbde16e0f3ebddf6d

Combustion Condition Identification though Flame Imaging and Convolutional Autoencoder

Autoři: Zewen QIAN Zhezhe HAN Haoran JIANG a další

Zdroj: IEICE Transactions on Information and Systems. :1283-1286

CAE SynthImgGen: Revolutionizing cancer diagnosis with convolutional autoencoder-based synthetic image generation

Autoři: Shivalila Hangaragi N. Neelima Vivek Venugopal a další

Zdroj: Alexandria Engineering Journal, Vol 115, Iss, Pp 343-354 (2025)

Témata: Synthetic image generation, SSIM, Convolutional autoencoder, Convolutional neural network, TA1-2040, Engineering (General). Civil engineering (General), Lung cancer classification

Přístupová URL adresa: https://doaj.org/article/aa4d4ade397444fc9203f24c4f07ede9

A turbulence reduced order model based on non-interpolated convolutional autoencoder

Autoři: WU Pin ZHANG Bo SONG Chao a další

Zdroj: Xibei Gongye Daxue Xuebao, Vol 43, Iss 1, Pp 149-153 (2025)

Témata: reduced-order model, non-interpolated convolutional autoencoder, reduced-dimensional reconstruction, TL1-4050, Motor vehicles. Aeronautics. Astronautics

Přístupová URL adresa: https://doaj.org/article/a60236e02ab0428a9bb44d6bbe63c9d5

Optimized Temporal Denoised Convolutional Autoencoder for Enhanced ADHD Classification Using fMRI Data

Autoři: Zarina Begum Kareemulla Shaik

Zdroj: IEEE Access, Vol 13, Pp 29031-29045 (2025)

Témata: Attention deficit hyperactivity disorder, optimized temporal denoised convolutional autoencoder, deep learning, adaptive osprey optimization, Electrical engineering. Electronics. Nuclear engineering, spatial features, fMRI images, TK1-9971

Přístupová URL adresa: https://doaj.org/article/a8ff8ca9acda4137b99f9fee50cebd36

River Channel Microgeomorphic Feature Extraction and Potential Sandstorm Source Identification Method Based on a Convolutional Autoencoder Model

Autoři: Kecong Wu Lirong Chen Yalige Bai a další

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 2602-2617 (2025)

Témata: convolutional autoencoder (CAE), Ocean engineering, QC801-809, Geophysics. Cosmic physics, microgeomorphic feature, Anomaly values, TC1501-1800, Yarlung Zangbo River, sandstorm sources

Přístupová URL adresa: https://doaj.org/article/94424c5cfbc34885963f0ffe4a93a78c

A performance analysis of convolutional autoencoder modified WaveGAN architectures for realistic 12 lead electrocardiogram synthesis

Autoři: Jiaqi Liu Kwok Tai Chui Lap-Kei Lee a další

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-22 (2025)

Témata: 12-Lead ECG synthesis, Convolutional autoencoder, Deep learning, ECG data generation, Feature extraction, Generative adversarial networks, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/dec4e72d30e840b98711653b47323356

PSO-MCAE-LCCD: Particle Swarm Optimized MobileNetV2 Convolutional Autoencoder for Lung and Colon Cancer Detection

Autoři: L.K. Suresh Kumar K. Srinivasa Chakravarthy M. Sathya Devi a další

Zdroj: International Journal of Environmental Sciences. :714-722

Multi-bearing fault diagnosis method based on convolutional autoencoder causal decoupling domain generalization

Autoři: Xinyang Cui Hongfei Zhan Kang Han a další

Zdroj: ISA Transactions. 163:236-250

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40368755

Deep Graph Convolutional Autoencoder With Conditional Normalizing Flow for Power Distribution Systems Fault Classification and Location

Autoři: Mohsen Saffari Mahdi Khodayar Mohammad E. Khodayar a další

Zdroj: IEEE Transactions on Artificial Intelligence. 6:2448-2463

Real-Time Monitoring and Analysis of Flame Combustion Optimized by Fusion Convolutional Autoencoder

Autoři: Ji, Hongxiang

Zdroj: Image Processing, Electronics and Computers. 75

Spatialsmooth: a spatially-aware convolutional autoencoder framework for enhanced deconvolution of spatial transcriptomics data

Autoři: Xiao Yang Jinjin Xiang Yanbin Feng a další

Zdroj: BMC Genomics, Vol 26, Iss 1, Pp 1-16 (2025)

Témata: Spatial transcriptomics, Deconvolution, Convolutional autoencoder, Positional encoding, Biotechnology, TP248.13-248.65, Genetics, QH426-470

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1471-2164

Přístupová URL adresa: https://doaj.org/article/cf4a010a44b741dc8353cf0daf6a29c4

Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder

Autoři: Shubham Chaudhry Azzedine Abdedou Azzeddine Soulaïmani

Zdroj: Advanced Modeling and Simulation in Engineering Sciences, Vol 12, Iss 1, Pp 1-23 (2025)

Témata: Reduced-order model, Convolutional autoencoder, Additive manufacturing, Deep learning, Proper orthogonal decomposition, Mechanics of engineering. Applied mechanics, TA349-359, Systems engineering, TA168

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2213-7467

Přístupová URL adresa: https://doaj.org/article/1acb9d02b46540cbb5ab687871ded7c0

Drug-target interaction prediction based on graph convolutional autoencoder with dynamic weighting residual GCN

Autoři: Ming Zeng Min Wang Fuqiang Xie a další

Zdroj: BMC Bioinformatics, Vol 26, Iss 1, Pp 1-29 (2025)

Témata: Drug-target interaction, Dynamic weighting convolutional residual connection, Dual self-supervised joint training mechanism, Graph convolutional autoencoder, Generative adversarial network, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1471-2105

Přístupová URL adresa: https://doaj.org/article/c9b441325e6d409dbc981ebfca8af0c6

ABCD: Trust Enhanced Attention based Convolutional Autoencoder for Risk Assessment

Autoři: Naidu, Sarala Mohan Xiong, Ning

Zdroj: ACM International Conference Proceeding Series. :301-310

Témata: Anomaly detection, Attentions, Calibration error, Convolutional Autoencoder, cooling liquid conductivity, Cooling systems, Industrial refrigeration, Risk assessment, Risk management, Self-supervised learning, Semi-supervised learning, Attention, Auto encoders, Cooling liquid, Industrial systems, Liquid conductivity, Risks assessments, Calibration

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-68572
https://doi.org/10.1145/3674029.3674076

A Multi-omics Cancer Subtype Clustering Method Based on Convolutional Autoencoder and Prototype Alignment

Autoři: Xianlong Lin Xiaoding Wang Weiquan Zeng a další

Zdroj: Communications in Computer and Information Science ISBN: 9789819501281

Convolutional Autoencoder and Deep Convolutional Neural Network Hybrid Model for Plant Disease Detection

Autoři: Prashant Govindrao Aher Vikrant Sabnis Jay Kumar Jain

Zdroj: Lecture Notes in Networks and Systems ISBN: 9789819657254

DeepCAI-V3: Improved Brain Tumor Classification from Noisy Brain MR Images Using Convolutional Autoencoder and Inception-V3 Architecture

Autoři: Babaferi, Evuarhere Vivian Fagbola, Temitayo Matthew Thakur, Colin Surendra

Zdroj: 2024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD). :1-7

Témata: InceptionV3, Transfer Learning, Brain Tumor Classification, MRI Denoising, Convolutional Autoencoder

Detection of Buried Landmines using a Convolutional Autoencoder trained on Simulated prompt Gamma Spectra

Autoři: Konstantinos KARAFASOULIS

Zdroj: Bulletin of "Carol I" National Defense University, Vol 14, Iss 2 (2025)

Témata: Neutron Activation, Gamma Radiation, Landmine Detection, Military Science, Artificial Intelligence, Anomaly Detection, Autoencoders, International relations, JZ2-6530

Přístupová URL adresa: https://doaj.org/article/88b87bc7ab854f759c7e1f0098baf8ec

Depression Detection Through EEG Signal Analysis: A Convolutional Autoencoder Deep Learning Model

Autoři: Neda Firoz Sergey Vladimirovich Aksyonov Olga Grigorievna Berestneva a další

Zdroj: 2025 IEEE 26th International Conference of Young Professionals in Electron Devices and Materials (EDM). :1820-1825