Výsledky vyhledávání - Multi-scale conventional autoencoder

Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system

Autoři: Teutsch, Philipp Pfeffer, Philipp Ghazijahani, Mohammad Sharifi a další

Témata: Physics - Fluid Dynamics, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2501.03070

Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

Autoři: Wang, Yao Lei, Xiujuan Chen, Yuli a další

Zdroj: International Journal of Molecular Sciences. Feb2025, Vol. 26 Issue 4, p1509. 20p.

Témata: *ARTIFICIAL neural networks, *CONVOLUTIONAL neural networks, *AUTOENCODERS, *CIRCULAR RNA, *DRUG target

Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system

Autoři: Philipp Teutsch Philipp Pfeffer Mohammad Sharifi Ghazijahani a další

Zdroj: APL Machine Learning, Vol 3, Iss 1, Pp 016112-016112-15 (2025)

Témata: Physics, QC1-999, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2770-9019

Přístupová URL adresa: https://doaj.org/article/236f8e1f2be64001a1d9c1d7b38ae1f2

Multi-scale asynchronous correlation and 2D convolutional autoencoder for adolescent health risk prediction with limited fMRI data

Autoři: Di Gao Guanghao Yang Jiarun Shen a další

Zdroj: Frontiers in Computational Neuroscience, Vol 18 (2024)

Témata: adolescence, health risk assessment, functional magnetic resonance imaging, deep learning, convolutional autoencoder, behavioral health risks, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fncom.2024.1478193/full; https://doaj.org/toc/1662-5188

Přístupová URL adresa: https://doaj.org/article/7e665edbb7b24faf972c7fe95a652ce0

IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks

Autoři: Suma Christal Mary Sundararajan Yamini Bhavani Shankar Sinthia Panneer Selvam a další

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-21 (2025)

Témata: Water quality prediction, Internet of things, Aquaponic fish ponds, Revamped fitness-based mother optimization algorithm, Multi-scale feature fusion-based convolutional autoencoder with gated recurrent unit, Medicine, Science

Popis souboru: electronic resource

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

Přístupová URL adresa: https://doaj.org/article/481247aba02e483987cf278ae390a214

Autoencoder-based Unsupervised Intrusion Detection using Multi-Scale Convolutional Recurrent Networks

Autoři: Singh, Amardeep Jang-Jaccard, Julian

Témata: Computer Science - Cryptography and Security, text

URL: http://arxiv.org/abs/2204.03779

Multi-scale Residual Segmentation Network for Histopathological Image.

Autoři: BOZDAĞ KARAKEÇİ, Zehra TALU, Muhammed Fatih

Zdroj: Dicle University Journal of Engineering / Dicle Üniversitesi Mühendislik Dergisi; eyl2024, Vol. 15 Issue 3, p623-632, 10p

Témata: CONVOLUTIONAL neural networks, DEEP learning, IMAGE segmentation, OBJECT recognition (Computer vision), AUTOENCODERS, PATHOLOGY, ARTIFICIAL neural networks, IMAGE processing, ARTIFICIAL intelligence, MARKOV random fields, TRAINING needs

A Variational Multi-Scale Error Compensation Network for Single-Pixel Imaging

Autoři: Jian Lin Qiurong Yan Quan Zou a další

Zdroj: IEEE Photonics Journal, Vol 16, Iss 4, Pp 1-11 (2024)

Témata: Single pixel imaging, deep learning, variational autoencoder, imaging reconstruction, Applied optics. Photonics, TA1501-1820, Optics. Light, QC350-467

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/10582416/; https://doaj.org/toc/1943-0655

Přístupová URL adresa: https://doaj.org/article/509f0c9832ec461ab53fa9d01fbfd372

Saliency supervised masked autoencoder pretrained salient location mining network for remote sensing image salient object detection.

Autoři: Fu, Yuxiang Fang, Wei Sheng, Victor S.

Zdroj: ISPRS Journal of Photogrammetry & Remote Sensing. Jun2025, Vol. 224, p222-234. 13p.

Témata: *ARTIFICIAL neural networks, *TRANSFORMER models, *OBJECT recognition (Computer vision), *CONVOLUTIONAL neural networks, *COMPUTER vision

Video Prediction Using Multi-Scale Deep Neural Networks

Autoři: N. Shayanfar V. Derhami M. Rezaeian

Zdroj: Journal of Artificial Intelligence and Data Mining, Vol 10, Iss 3, Pp 423-431 (2022)

Témata: deep learning, convolutional autoencoder, video prediction, multiscale processing, Information technology, T58.5-58.64, Computer software, QA76.75-76.765

Popis souboru: electronic resource

Relation: https://jad.shahroodut.ac.ir/article_2482_6f40144a42fafdceaf29a6dbe1fa98f0.pdf; https://doaj.org/toc/2322-5211; https://doaj.org/toc/2322-4444

Přístupová URL adresa: https://doaj.org/article/ee1d814d37d348a4b665df01edd66f4c

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders.

Autoři: Sajid, Muhammad Razzaq Malik, Kaleem Ur Rehman, Ateeq a další

Zdroj: Scientific Reports. 1/25/2025, Vol. 15 Issue 1, p1-18. 18p.

Témata: *NATURAL language processing, *ARTIFICIAL intelligence, *TRANSFORMER models, *COGNITIVE psychology, *ELECTRONIC data processing

Trans-cVAE-GAN: Transformer-Based cVAE-GAN for High-Fidelity EEG Signal Generation.

Autoři: Yao, Yiduo Wang, Xiao Hao, Xudong a další

Zdroj: Bioengineering (Basel). Oct2025, Vol. 12 Issue 10, p1028. 40p.

Témata: *ELECTROENCEPHALOGRAPHY, *GENERATIVE adversarial networks, *TRANSFORMER models, *BRAIN-computer interfaces, *AFFECTIVE computing, *PROBABILISTIC generative models, *EMOTION recognition

ModuCLIP: multi-scale CLIP framework for predicting foundation pit deformation in multi-modal robotic systems.

Autoři: Wenbo, Lin Tingting, Li Xiao, Li

Zdroj: Frontiers in Neurorobotics; 2025, p1-19, 19p

Témata: MACHINE learning, BUILDING foundations, INDUSTRIAL safety, ROBOTICS, COMPUTER simulation, DEEP learning

Detecting network intrusions in cyber-physical systems using deep autoencoder-based dimensionality reduction approach and deep neural networks.

Autoři: Ibor, A. E. Egete, D. O. Otiko, A. O. a další

Zdroj: Journal of Nigerian Society of Physical Sciences; Aug2025, Vol. 7 Issue 3, p1-15, 15p

Témata: ARTIFICIAL neural networks, FEEDFORWARD neural networks, AUTOENCODERS, CYBER physical systems, COMPUTER network traffic, DEEP learning

Performance enhancement in hydroponic and soil compound prediction by deep learning techniques

Autoři: Mustufa Haider Abidi Sanjay Chintakindi Ateekh Ur Rehman a další

Zdroj: PeerJ Computer Science, Vol 10, p e2101 (2024)

Témata: Hydroponic and soil compound prediction, Plant growth, Weighted features, Iteration-assisted enhanced mother optimization algorithm, Multi-scale feature fusion-based convolution autoencoder with gated recurrent unit, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://peerj.com/articles/cs-2101.pdf; https://peerj.com/articles/cs-2101/; https://doaj.org/toc/2376-5992

Přístupová URL adresa: https://doaj.org/article/23660b5531f14c868a86f5405575af7e

Efficient multiscale weighted features based residual ConvLSTM method to detect Parkinson's disease using electroencephalogram data.

Autoři: Rajesh Kumar, K. Ganesh Babu, T.R.

Zdroj: Biomedical Signal Processing & Control. Nov2025, Vol. 109, pN.PAG-N.PAG. 1p.

Témata: Long short-term memory, Parkinson's disease, Optimization algorithms, Feature extraction, Autoencoder, Deep learning

Multi-scale Spatial-temporal Interaction Network for Video Anomaly Detection

Autoři: Ning, Zhiyuan Li, Zhangxun Guo, Zhengliang a další

Témata: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2306.10239

An Improved Capsule Network for Image Classification Using Multi-Scale Feature Extraction.

Autoři: Huang, Wenjie Kang, Ruiqing Li, Lingyan a další

Zdroj: Journal of Imaging; Oct2025, Vol. 11 Issue 10, p355, 28p

A convolutional autoencoder model with weighted multi-scale attention modules for 3D skeleton-based action recognition.

Autoři: Khezerlou, F. Baradarani, A. Balafar, M.A.

Zdroj: Journal of Visual Communication & Image Representation. Apr2023, Vol. 92, pN.PAG-N.PAG. 1p.

Témata: *THREE-dimensional imaging, *SKELETON, *JOINTS (Anatomy), *TRAJECTORIES (Mechanics), *SPATIOTEMPORAL processes

A multimodal fusion network based on variational autoencoder for distinguishing SCLC brain metastases from NSCLC brain metastases.

Autoři: Linyan X Jie C Kexuan Z a další

Zdroj: Medical physics [Med Phys] 2025 Jul; Vol. 52 (7), pp. e17816. Date of Electronic Publication: 2025 May 02.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: John Wiley and Sons, Inc Country of Publication: United States NLM ID: 0425746 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2473-4209 (Electronic) Linking ISSN: 00942405 NLM ISO Abbreviation: Med Phys Subsets: MEDLINE

Výrazy ze slovníku MeSH: Brain Neoplasms*/secondary , Brain Neoplasms*/diagnostic imaging , Carcinoma, Non-Small-Cell Lung*/pathology , Carcinoma, Non-Small-Cell Lung*/diagnostic imaging , Lung Neoplasms*/pathology , Small Cell Lung Carcinoma*/diagnostic imaging , Small Cell Lung Carcinoma*/pathology , Image Processing, Computer-Assisted*/methods, Humans ; Diagnosis, Differential ; Magnetic Resonance Imaging ; Autoencoder