Výsledky vyhľadávania - "Convolution Neural Networks"

Biomineralization Induction for 3D Bioprinted Osteogenic Structures Informed by Bioimaging-Biomodelling Techniques Through Geometrical Efficiency, and Hydrogel Optimization

Autori: Abdallah, Yomna Khalid Ibrahim Mohammed

Prispievatelia: University/Department: Universitat Internacional de Catalunya. Departament d'Arquitectura

Thesis Advisors: Estevez, Alberto T., Mozafari, Masoud

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Biomineralization, Hydrogel, Micro Computed Tomography, Rheological Properties, Bone- Imagine, Convolution Neural Networks, 3D Diffusion Models, Biomimetic Scaffold Design, Bioingeniería

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/694251

A new state-of-the-art technique for textural and structural microimager data analysis using deep learning algorithms

Autori: G. A. Kossov V. V. Abashkin S. S. Egorov a ďalší

Zdroj: Georesursy, Vol 0, Iss 0 (2024)

Predmety: convolution neural networks, QE1-996.5, quantitative geological interpretation, borehole formation microimager, Geology, automated interpretation, computer vision

Prístupová URL adresa: https://doaj.org/article/36a8fee166524b3d9be3947bf6992699

Breast Cancer Detection Using Mammography: Image Processing to Deep Learning

Autori: Shahzad Ahmad Qureshi null Aziz-Ul-Rehman Lal Hussain a ďalší

Zdroj: IEEE Access, Vol 13, Pp 60776-60801 (2025)

Predmety: Breast cancer, Mammography, Microcalcification, Deep learning, Convolution neural networks, Machine learning, microcalcification, convolution neural networks, machine learning, mammography, deep learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis súboru: application/pdf

Prístupová URL adresa: https://doaj.org/article/1323c6fa32bd46418ae14485147f582f
https://hdl.handle.net/11583/2996605
https://ieeexplore.ieee.org/document/10817580
https://doi.org/10.1109/access.2024.3523745

A generative adversarial network optimization method for damage detection and digital twinning by deep AI fault learning:Z24 Bridge structural health monitoring benchmark validation

Autori: Impraimakis, Marios Palkanoglou, Evangelia Nektaria

Zdroj: Impraimakis, M & Palkanoglou, E N 2025, 'A generative adversarial network optimization method for damage detection and digital twinning by deep AI fault learning : Z24 Bridge structural health monitoring benchmark validation', Structural and Multidisciplinary Optimization, vol. 68, no. 11, 221, pp. 1-21. https://doi.org/10.1007/s00158-025-04162-0

Predmety: Artificial intelligence, name=Engineering(all), Data augmentation, Fault anomaly detection, Support vector machine (SVM) classifier, Digital twinning of damage states, name=SDG 9 - Industry, Innovation, and Infrastructure, Unsupervised learning, Conditional-labeled GANs, Pattern recognition, Infrastructure resilience, Benchmark validation, name=SDG 13 - Climate Action, Civil engineering, Generative adversarial networks (GANs), Controlled damage experiment, 1D convolutional neural networks (1D CNNs), convolution neural networks, Physics-informed AI, Unsupervised fault learning, Deep learning, Nondestructive testing (NDT), Damage detection, structural dynamics, Digital twin, Vibration-based monitoring, Structural health monitoring optimization, Post-tensioned concrete bridge, structural engineering, name=Computer Science(all), Principal component analysis (PCA), mechanical engineering, vibration, name=SDG 11 - Sustainable Cities and Communities, Z24 Bridge dataset

Popis súboru: application/pdf

Prístupová URL adresa: https://purehost.bath.ac.uk/ws/files/377052118/s00158-025-04162-0.pdf

Hyb_LSTM+KCNN: Hybrid Long Short Term Memory with Kernel Convolution Neural Networks Based Time Series Forecasting for Air Quality Index Detection

Autori: Jacob, Suma Sira Aldehim, Ghadah Maashi, Mashael a ďalší

Zdroj: Tehnicki vjesnik - Technical Gazette. 32

Predmety: convolution neural networks, time series model, long short term memory, forcasting, air quality

Popis súboru: application/pdf

Prístupová URL adresa: https://hrcak.srce.hr/335044
https://doi.org/10.17559/tv-20240828001947

Efficient and Deployable Violence Detection using Transfer Learning Framework for Public Safety

Autori: Sanam Narejo Shabana Hajano Anoud Shaikh a ďalší

Zdroj: Mehran University Research Journal of Engineering and Technology, Vol 44, Iss 4, Pp 01-16 (2025)

Predmety: smart city, violence detection, transfer learning, closed-circuit television, convolution neural networks, artificial intelligence, Technology, Engineering (General). Civil engineering (General), TA1-2040, Science

Popis súboru: electronic resource

Relation: https://murjet.muet.edu.pk/index.php/home/article/view/125; https://doaj.org/toc/0254-7821; https://doaj.org/toc/2413-7219

Prístupová URL adresa: https://doaj.org/article/5371452653ff484c9fe54f7bcffcb2a6

Renal Cancer Classification in Tomographic Images Using Convolutional Neural Networks to Assist Early Diagnosis

Autori: Vinícius Meireles Pereira Santos Ana Claudia Patrocinio William Chaves de Souza Carvalho a ďalší

Zdroj: Revista de Informática Teórica e Aplicada; Vol. 32 No. 1 (2025); 61-66
Revista de Informática Teórica e Aplicada; v. 32 n. 1 (2025); 61-66

Predmety: Convolution Neural Networks, Classification of Kidney Images, deep learning, kidney cancer, Kidney Cancer, cnn

Popis súboru: application/pdf

Prístupová URL adresa: https://seer.ufrgs.br/index.php/rita/article/view/143539

Desarrollo de competencias: inteligencia artificial y aprendizaje automático en prácticas supervisadas de estudiantes en computación

Autori: Johnny Villalobos-Murillo Gabriela Garita-González Byron Jesús Alfaro Ramírez

Zdroj: Uniciencia, Vol 39, Iss 1, Pp 1-19 (2025)
Uniciencia, Volume: 39, Issue: 1, Pages: 32-50, Published: 19 MAR 2025

Predmety: Artificial intelligence, convolution neural networks, knowledge, Science (General), redes neurais de convolução, inteligencia artificial, computación e informática, Science, computação e informática, Machine Learning, Q1-390, machine learning, aprendizagem automática, conhecimento, redes neuronales de convolución, aprendizaje automático, inteligência artificial, Computer Science and Information Technology, conocimiento

Popis súboru: text/html

Prístupová URL adresa: https://doaj.org/article/d3bd05d9070d47499e753f53a7e2a04a
http://www.scielo.sa.cr/scielo.php?script=sci_arttext&pid=S2215-34702025000100032&lng=en&tlng=en

Graph Split Federated Learning for Distributed Large-Scale AIoT in Smart Cities

Autori: Hanyue Xu Kah Phooi Seng Li-Minn Ang a ďalší

Zdroj: IEEE Open Journal of the Computer Society, Vol 6, Pp 1027-1040 (2025)

Predmety: Electronic computers. Computer science, QA75.5-76.95, Information technology, artificial intelligence internet of things, distributed collaborative machine learning, T58.5-58.64, graph convolution neural networks, Split federated learning, passenger demand forecasting

Prístupová URL adresa: https://doaj.org/article/a1de1a2285df4b0b9d778a978009e686

Ordinal METAR Cloud Cover Classification in Sentinel-2 Satellite Data

Autori: Markus Götz Erik Wessel Uğur Çayoğlu a ďalší

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 10674-10683 (2025)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 10674–10683

Predmety: Ocean engineering, Earth sciences, machine learning, ddc:550, QC801-809, sentinel-2, Geophysics. Cosmic physics, Convolution neural networks, ordinal classification, TC1501-1800, satellite images, meteorological aerodrome report (METAR)

Popis súboru: application/pdf

Prístupová URL adresa: https://doaj.org/article/181092b73ce346d4b9e4a613b56d730c
https://publikationen.bibliothek.kit.edu/1000180808
https://publikationen.bibliothek.kit.edu/1000180808/158669201
https://doi.org/10.5445/IR/1000180808

Wind Turbine Blades Fault Diagnosis Based on Vibration Signals Utilizing Convolutional Neural Network

Autori: Bougoffa, Mouaad Benmoussa, Samir Djeziri, Mohand a ďalší

Prispievatelia: Bougoffa, Mouaad Benmoussa, Samir Djeziri, Mohand a ďalší

Zdroj: 2024 International Conference on Decision Aid Sciences and Applications (DASA). :1-5

Predmety: Vibration signals, [SPI] Engineering Sciences [physics], Wind Turbine, Convolution Neural Networks, [INFO] Computer Science [cs], Fault Diagnosis

Popis súboru: application/pdf

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model

Autori: Soliman, Amira Chang, Jose R. Etminani, Kobra a ďalší

Zdroj: BMC Medical Informatics and Decision Making. 22:1-15

Predmety: Brain Neurodegenerative Disorders, Convolution Neural Networks, Medical Image Classification, Transfer Learning

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-49079
https://doi.org/10.1186/s12911-022-02054-7

Very short-term solar radiation forecasting with all-sky images and meteorological data

Autori: Trinh Trung Hieu Nguyen Binh Nam Duong Minh Quan a ďalší

Zdroj: Tạp chí Khoa học và Công nghệ, Pp 130-134 (2025)

Predmety: renewable energy, all-sky image, convolution neural networks, long short-term memory, very short-term forecasting, Technology

Popis súboru: electronic resource

Relation: https://jst-ud.vn/jst-ud/article/view/10226; https://doaj.org/toc/1859-1531

Prístupová URL adresa: https://doaj.org/article/76f7856440874d8aa51d03cc0467e58e

A machine learning approach for epileptic seizure detection using BEMD and long short term memory neural networks

Autori: Ranjith Gopalakrishnan Vijay Franklin John Bosco Martin Rajesh Kanna Panner

Zdroj: AKCE International Journal of Graphs and Combinatorics, Pp 1-10 (2025)

Predmety: Epilepsy, electroencephalogram, convolution neural networks, bi-dimensional empirical mode decomposition and long short-term memory, Mathematics, QA1-939

Popis súboru: electronic resource

Relation: https://doaj.org/toc/0972-8600; https://doaj.org/toc/2543-3474

Prístupová URL adresa: https://doaj.org/article/e13242ea8d6447779e3bd8d43d729780

Innovative computer vision methods for tomato (Solanum Lycopersicon) detection and cultivation: a review

Autori: L. Moldvai A. Nyéki

Zdroj: Discover Applied Sciences, Vol 7, Iss 9, Pp 1-56 (2025)

Predmety: Computer vision (CV), Convolution neural networks (CNN), Vision transformers (ViT), Deep learning (DL), Tomato detection and cultivation, Science (General), Q1-390

Popis súboru: electronic resource

Relation: https://doaj.org/toc/3004-9261

Prístupová URL adresa: https://doaj.org/article/3c9914d4fc8f4d06bd0ae4d6f35e83d2

Deep nested U-structure network with frequency attention for building semantic segmentation

Autori: Khaled Moghalles Zaid Al-Huda Dalal AL-Alimi a ďalší

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-16 (2025)

Predmety: Building extraction, Residual U-structure, Remote sensing, Convolution neural networks, Medicine, Science

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/0025f7a2a7fb40f58ff531db809a7a10

Enhancing dysarthria severity classification: efficient audio based deep learning models

Autori: Varsha J Varma Aniruddha Jana Arpan Kumar Samal a ďalší

Zdroj: Discover Applied Sciences, Vol 7, Iss 8, Pp 1-25 (2025)

Predmety: Mel-spectrogram, Short-time Fourier transform (STFT), Dysarthria diagnosis, Convolution neural networks, Gated recurrent unit, Long short-term memory, Science (General), Q1-390

Popis súboru: electronic resource

Relation: https://doaj.org/toc/3004-9261

Prístupová URL adresa: https://doaj.org/article/496ace39dc9a418fac512f74fe18b285

Pilot study: a low-cost, point-of-care microfluidic chip for smartphone-integrated colorimetric detection using convolutional neural networks

Autori: Mithun Kanchan Pedapudi Anantha Hari Arun Siddhant Rakesh Chutke

Zdroj: Discover Applied Sciences, Vol 7, Iss 8, Pp 1-15 (2025)

Predmety: Colorimetry, Convolution neural networks, Deep learning, Glucose, Microfluidics, Smartphone, Science (General), Q1-390

Popis súboru: electronic resource

Relation: https://doaj.org/toc/3004-9261

Prístupová URL adresa: https://doaj.org/article/6b9bb3346f8244e3aed4a0e8db0b253e

AI and Inverse Methods for Building Digital Twins in Neuroscience

Autori: Nogaret, Alain Mirallave-Pescador, Ana Kschischo, Maik

Zdroj: Nogaret, A, Mirallave-Pescador, A & Kschischo, M 2025, 'AI and Inverse Methods for Building Digital Twins in Neuroscience', Frontiers in Computational Neuroscience, vol. 19, 1684335. https://doi.org/10.3389/fncom.2025.1684335

Predmety: neuroscience, convolution neural networks (CNN), deep learning–artificial intelligence, name=Cellular and Molecular Neuroscience, data assimilation (DA), recurrent neural networks (RNN), name=Neuroscience (miscellaneous)

Popis súboru: application/pdf

Prístupová URL adresa: https://purehost.bath.ac.uk/ws/files/372555592/Editorial_Front_Comp_Neurosci.pdf

A COMPARATIVE ANALYSIS OF DEEP TRANSFER LEARNING TECHNIQUES FOR MAMMOGRAPHIC IMAGE CLASSIFICATION

Autori: Bhavesh Gupta Akshay Singh Anjana Gosain

Zdroj: Proceedings on Engineering Sciences, Vol 6, Iss 4, Pp 1879-1888 (2024)

Predmety: convolution neural networks, breast cancer, deep transfer learning, TA1-2040, Engineering (General). Civil engineering (General), mammography image classification

Prístupová URL adresa: https://doaj.org/article/47332dc8f1244549b3f9f9bb780d1e21