Search Results - deep convolutional autoencoder model

Deep Convolutional Autoencoder Model for Urban Land Use Classification using Mobile Device Data

Authors: Sun, Zhihao Peng, Zhenghiong Yu, Yang et al.

Subject Terms: Urban Land Use Classification, Deep learning, Convolutional Autoencoder Model, Mobile Device Data, Call Detail Records, 11. Sustainability, 15. Life on land

High performance computing and artificial intelligence algorithms for dimensionality reduction of turbulent flows

Authors: Eiximeno Franch, Benet

Contributors: University/Department: Universitat Politècnica de Catalunya. Departament de Física

Thesis Advisors: Rodríguez Pérez, Ivette María, Lehmkuhl Barba, Oriol

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: reduced order models, high performance computing, deep learning, singular value decomposition, variational autoencoders, Àrees temàtiques de la UPC::Física, Àrees temàtiques de la UPC::Informàtica, 531/534 - Mecànica. Vibracions. Acústica, 004 - Informàtica

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/695826
https://dx.doi.org/10.5821/dissertation-2117-446576

Detection, quantification, malignancy prediction and growth forecasting of pulmonary nodules using deep learning in follow-up CT scans

Authors: Rafael-Palou, Xavier

Contributors: University/Department: Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions

Thesis Advisors: González Ballester, Miguel Ángel, Piella Fenoy, Gemma, Ribas Ripoll, Vicent Jordi

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Lung cancer prediction, Nodule detection, Nodule segmentation, Nodule characterization, Nodule malignancy estimation, Nodule follow-up, Nodule re-identification, Nodule growth forecasting, Uncertainty modelling and quantification, Convolutional neural networks, Variational autoencoders, Siamese neural networks, Generative networks, Transfer learning, Computer vision, Deep learning, Machine learning, Predicció del càncer de pulmó, Detecció de nòduls, Segmentació de nòduls, Caracterització de nòduls, Predicció de malignitat de nòduls, Seguiment de nòduls, Re-identificació de nòduls, Creixement de nòduls, Modelatge i quantificació de la malignitat, Xarxes neuronals convolucionals, Autoencoders variacional, Xarxes neuronals siameses, Xarxes generatives, Aprenentatge per transferència, Pipelines, Visió per computador, Aprenentatge profund, Aprenentatge automàtic

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/672964

SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography

Authors: Bardia Yousefi Hamed Akbari Michelle Hershman et al.

Source: Applied Sciences, Vol 11, Iss 7, p 3248 (2021)

Subject Terms: breast cancer, thermography, sparse deep convolutional autoencoder, matrix factorization, dimensionality reduction, thermomics, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

File Description: electronic resource

Relation: https://www.mdpi.com/2076-3417/11/7/3248; https://doaj.org/toc/2076-3417

Access URL: https://doaj.org/article/3c70757effa743f3b9bef5e4d264eb2f

A hybrid 1DCNN-GRU deep learning framework for classifying caprine granulosa cell fertility potential using single-cell transcriptomics.

Authors: Sananmuang, Thanida Puthier, Denis Chokeshaiusaha, Kaj

Source: Veterinary World. Jul2025, Vol. 18 Issue 7, p1922-1935. 14p.

Subjects: Granulosa cells, Fertility, Convolutional neural networks, Transcriptomes, Deep learning, Recurrent neural networks, Goats, Biomarkers

The Model Is the Message: Lightweight Convolutional Autoencoders Applied to Noisy Imaging Data for Planetary Science and Astrobiology

Authors: Caleb Scharf

Source: Icarus.

Subject Terms: Exobiology, Astronomy

Access URL: https://ntrs.nasa.gov/citations/20250004413

An Aquatic Image Compression Scheme based on Optimized Deep Convolutional Autoencoder.

Authors: Pau, Raj Kumar Vishwakarma, Ankit Chandran, Saravanan

Source: IAENG International Journal of Computer Science. Feb2024, Vol. 51 Issue 2, p83-90. 8p.

Subject Terms: Image compression, Generative adversarial networks, Computer network traffic, Convolutional neural networks, Data compression, Deep learning

Convolution Autoencoder based Classification Model for Content Based Image Retrieval.

Authors: Rai, Rishi Sisodia, Dilip Singh

Source: Procedia Computer Science. 2025, Vol. 258, p1865-1876. 12p.

Subject Terms: Content-based image retrieval, Convolutional neural networks, Image recognition (Computer vision), Autoencoders, Binary codes, Deep learning

Deep Convolutional Autoencoder Model for Urban Land Use Classification using Mobile Device Data ; Deep convolutional Autoencoder Model for Urban Land Use Classification using Mobile Device Data

Authors: Sun, Zhihao Peng, Zhenghiong Yu, Yang et al.

Subject Terms: Urban Land Use Classification, Deep learning, Convolutional Autoencoder Model, Mobile Device Data, Call Detail Records, geo, demo

Relation: https://zenodo.org/record/6513201

Availability: https://zenodo.org/record/6513201

Shedding light on sewer pipes : deep learning perception approaches for autonomous sewer robots

Authors: Plana Rius, Ferran

Contributors: University/Department: Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial

Thesis Advisors: Mirats Tur, Josep Maria, Casas, Marc, Angulo Bahón, Cecilio

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Àrees temàtiques de la UPC::Informàtica

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/689536
https://dx.doi.org/10.5821/dissertation-2117-398049

Findings from Department of Computer Sciences and Engineering Yields New Data on Cardiovascular Diseases and Conditions (Self-attention-based Deep Convolutional Sparse Dense Autoencoder Model With Chebyshev-based Osprey Algorithm for...).

Source: Cardiovascular Week; 10/13/2025, p364-364, 1p

Subject Terms: CARDIOVASCULAR diseases, CONVOLUTIONAL neural networks, FEATURE extraction, DATA analysis, STATISTICAL accuracy, DEEP learning, ELECTROCARDIOGRAPHY, MEDICAL screening

Deep convolutional autoencoder for urban land use classification using mobile device data.

Authors: Sun, Zhihao Peng, Zhenghong Yu, Yang et al.

Source: International Journal of Geographical Information Science. Nov2022, Vol. 36 Issue 11, p2138-2168. 31p.

Subject Terms: Urban land use, Zoning, Urban planning, Urban policy, Cell phones, Time series analysis

Geographic Terms: Wuhan (China), China

Classification of Atypical White Blood Cells in Acute Myeloid Leukemia Using a Two-Stage Hybrid Model Based on Deep Convolutional Autoencoder and Deep Convolutional Neural Network.

Authors: Elhassan, Tusneem A. Mohd Rahim, Mohd Shafry Siti Zaiton, Mohd Hashim et al.

Source: Diagnostics (2075-4418); Jan2023, Vol. 13 Issue 2, p196, 20p

Subject Terms: LEUKOCYTES, ACUTE myeloid leukemia, CONVOLUTIONAL neural networks, MYELOID cells, MORPHOLOGY

Discovering Operational Patterns Using Image-Based Convolutional Clustering and Composite Evaluation: A Case Study in Foundry Melting Processes.

Authors: Ma, Zhipeng Jørgensen, Bo Nørregaard Ma, Zheng Grace

Source: Information. Sep2025, Vol. 16 Issue 9, p816. 31p.

Subject Terms: *Metadata, *Feature extraction, *Quantitative research, *Operations research, Manufacturing processes, Clustering algorithms, Process optimization, Deep learning

A Blind Convolutional Deep Autoencoder for Spectral Unmixing of Hyperspectral Images Over Waterbodies

Authors: Estefanıa Alfaro-Mejıa Vidya Manian Joseph D. Ortiz et al.

Source: Frontiers in Earth Science. 11

Subject Terms: Earth Resources and Remote Sensing

Access URL: https://ntrs.nasa.gov/citations/20230008862

AI-Powered Radiomics for Breast Cancer Prognosis and Aggressiveness Assessment via Ultrasound Imaging

Authors: Issam Ismail Zaidkilani, Nadeem

Thesis Advisors: García García, Miguel Angel, Puig Valls, Domènec Savi

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Càncer de Mama - Imatges per Ultrasò, Anàlisi d'Imatges Mèdiques, Diagnòstic Assistit per Ordinador (CAD), Cáncer de Mama - Imágenes por Ultrasonido, Análisis de Imágenes Médicas, Diagnóstico Asistido por Computadora (CAD), Breast Cancer-Ultrasound, Medical Image Analysis, Computer-Aided Diagnosis (CAD), Ciències

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/695647

Fast and scalable distributed deep convolutional autoencoder for fMRI big data analytics

Authors: Milad Makkie Heng Huang Yu Zhao et al.

Source: Neurocomputing. 325:20-30

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Machine Learning (stat.ML), Machine Learning (cs.LG), 03 medical and health sciences, 0302 clinical medicine, Computer Science - Distributed, Parallel, and Cluster Computing, Statistics - Machine Learning, Quantitative Biology - Neurons and Cognition, FOS: Biological sciences, Neurons and Cognition (q-bio.NC), Distributed, Parallel, and Cluster Computing (cs.DC), Neural and Evolutionary Computing (cs.NE)

Access URL: https://europepmc.org/articles/pmc6660166?pdf=render
https://pubmed.ncbi.nlm.nih.gov/31354187
http://arxiv.org/abs/1710.08961
http://arxiv.org/pdf/1710.08961.pdf
https://dblp.uni-trier.de/db/journals/corr/corr1710.html#abs-1710-08961
https://arxiv.org/abs/1710.08961
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660166
https://pubmed.ncbi.nlm.nih.gov/31354187/
http://www.diva-portal.org/smash/record.jsf?pid=diva2:1255524

Conditioned fully convolutional denoising autoencoder for multi-target NILM

Authors: García, Diego Pérez, Daniel Papapetrou, Panagiotis et al.

Source: Neural Computing & Applications. 37(17):10491-10505

Subject Terms: Non-intrusive Load Monitoring, Energy Efficiency, Deep Convolutional Neural Networks, Interpretability, Multi-target NILM models, data- och systemvetenskap, Computer and Systems Sciences

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-237967
https://doi.org/10.1007/s00521-024-10552-0

A deep learning framework for characterization of genotype data

Authors: Ausmees, Kristiina Nettelblad, Carl

Source: eSSENCE - An eScience Collaboration G3. 12(3)

Subject Terms: deep learning, convolutional autoencoder, dimensionality reduction, genetic clustering, population genetics, Beräkningsvetenskap, Scientific Computing

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-470290
https://doi.org/10.1093/g3journal/jkac020

Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises

Authors: Yan, Shen Shao, Haidong Xiao, Yiming et al.

Source: Robotics and Computer-Integrated Manufacturing. 79

Subject Terms: Machine tools, Deep learning, Unsupervised anomaly detection, Hybrid robust convolutional autoencoder, Noises, Drift och underhållsteknik, Operation and Maintenance

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-92934