Výsledky vyhledávání - "neural network with encoder-decoder architecture"

An intelligent speech enhancement model using enhanced heuristic-based residual convolutional neural network with encoder-decoder architecture

Autoři: M. Balasubrahmanyam R. S. Valarmathi

Zdroj: International Journal of Speech Technology. 27:637-656

Analysis of the effectiveness of two different loss functions in training a neural network in lung image reconstruction using impedance tomography

Autoři: Malgorzata Lalak-Dybała Barbara Stefaniak Paweł Olszewski

Zdroj: Journal of Modern Science, Vol 57, Iss 3, Pp 594-608 (2024)

Témata: 0301 basic medicine, neural network with encoder-decoder architecture, 03 medical and health sciences, resnet, 0202 electrical engineering, electronic engineering, information engineering, convolutional neural network, Social Sciences, 02 engineering and technology, lung reconstruction, electrical impedance tomography

Přístupová URL adresa: https://doaj.org/article/080fe2c0e5ff4f89b9924bad2ae2f2e4

An intelligent speech enhancement model using enhanced heuristic-based residual convolutional neural network with encoder-decoder architecture.

Autoři: Balasubrahmanyam, M. Valarmathi, R. S.

Zdroj: International Journal of Speech Technology; Sep2024, Vol. 27 Issue 3, p637-656, 20p

Témata: CONVOLUTIONAL neural networks, INTELLIGIBILITY of speech, SPEECH perception, SPEECH enhancement, HEARING aids, DEEP learning, SUPERVISED learning, SPEECH

Exhale-Focused Thermal Image Segmentation Using Optical Flow-Based Frame Filtering and Transformer-Aided Deep Networks.

Autoři: Lee, Do-Kyeong Shin, Jae-Sung Choi, Jae-Sung a další

Zdroj: Bioengineering (Basel); May2025, Vol. 12 Issue 5, p542, 17p

Témata: CONVOLUTIONAL neural networks, THERMOGRAPHY, TRANSFORMER models, IMAGE segmentation, COVID-19 pandemic, OPTICAL flow

Recurrent and Concurrent Prediction of Longitudinal Progression of Stargardt Atrophy and Geographic Atrophy towards Comparative Performance on Optical Coherence Tomography as on Fundus Autofluorescence.

Autoři: Mishra, Zubin Wang, Ziyuan Chris Xu, Emily a další

Zdroj: Applied Sciences (2076-3417); Sep2024, Vol. 14 Issue 17, p7773, 16p

Témata: CONVOLUTIONAL neural networks, ARTIFICIAL neural networks, OPTICAL coherence tomography, DRUG efficacy, THREE-dimensional imaging

Deep learning and machine learning‐based early survival predictions of glioblastoma patients using pre‐operative three‐dimensional brain magnetic resonance imaging modalities.

Autoři: Kaur, Gurinderjeet Rana, Prashant Singh Arora, Vinay

Zdroj: International Journal of Imaging Systems & Technology; Jan2023, Vol. 33 Issue 1, p340-361, 22p

Témata: MAGNETIC resonance imaging, MACHINE learning, DEEP learning, CONVOLUTIONAL neural networks, BRAIN tumors, GLIOBLASTOMA multiforme

OpenLabCluster: active learning based clustering and classification of animal behaviors based on kinematic body keypoints.

Autoři: Li, Jingyuan Keselman, Moishe Shlizerman, Eli

Zdroj: Frontiers in Systems Neuroscience; 2025, p1-13, 13p

Témata: ACTIVE learning, ANIMAL behavior, CLASSIFICATION, BEHAVIORAL assessment, POSE estimation (Computer vision), CLUSTERING algorithms

Bridging multimodal microscopy for advanced characterization on nuclear fuel using machine learning.

Autoři: Manda, Haarika Zhao, Liang Reddy Kancharla, Rahul a další

Zdroj: Frontiers in Mechanical Engineering; 2025, p1-10, 10p

Témata: URANIUM, MACHINE learning, DEEP learning, KNOWLEDGE transfer, MICROSTRUCTURE, NUCLEAR fuels, MICROSCOPY, IMAGE segmentation

Kairos: Practical Intrusion Detection and Investigation using Whole-system Provenance

Autoři: Cheng, Zijun Lv, Qiujian Liang, Jinyuan a další

Témata: Computer Science - Cryptography and Security, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2308.05034

Monocular 3D Human Pose Estimation for REBA Ergonomics: A Critical Review of Recent Advances.

Autoři: Bataineh, Ahmad Mwfaq Mohamed, Ahmad Sufril Azlan

Zdroj: Computers, Materials & Continua; 2025, Vol. 84 Issue 1, p93-124, 32p

Témata: ARTIFICIAL neural networks, COMPUTER vision, EVIDENCE gaps, DEEP learning, TWO-dimensional models

Improving Visual Speech Enhancement Network by Learning Audio-visual Affinity with Multi-head Attention

Autoři: Xu, Xinmeng Wang, Yang Jia, Jie a další

Témata: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Multimedia, Computer Science - Sound, text

URL: http://arxiv.org/abs/2206.14964

Data-Driven Linear Koopman Embedding for Networked Systems: Model-Predictive Grid Control

Autoři: Hossain, Ramij R. Adesunkanmi, Rahmat Kumar, Ratnesh

Témata: Electrical Engineering and Systems Science - Systems and Control, Computer Science - Artificial Intelligence, Mathematics - Optimization and Control, text

URL: http://arxiv.org/abs/2206.01272

AMFFCN: Attentional Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement

Autoři: Xu, Xinmeng Hao, Jianjun

Témata: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound, text

URL: http://arxiv.org/abs/2101.06268

Attention-based deep learning models for predicting anomalous shock of wastewater treatment plants.

Autoři: Zhang, Yituo Wang, Jihong Li, Chaolin a další

Zdroj: Water Research. May2025, Vol. 275, pN.PAG-N.PAG. 1p.

Témata: *LONG short-term memory, *DEEP learning, *SEWAGE disposal plants, *POLYWATER, *CHEMICAL oxygen demand

Editorial: Machine Learning Methods for High-Level Cognitive Capabilities in Robotics.

Autoři: Taniguchi, Tadahiro Ugur, Emre Ogata, Tetsuya a další

Zdroj: Frontiers in Neurorobotics; 10/22/2019, p1-3, 3p

Témata: COGNITIVE robotics, MACHINE learning, PROBABILISTIC generative models, ROBOT motion, ROBOT programming, HUMAN behavior

AutoML Segmentation for 3D Medical Image Data: Contribution to the MSD Challenge 2018

Autoři: Rippel, Oliver Weninger, Leon Merhof, Dorit

Témata: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2005.09978

A Registration Method for Historical Maps Based on Self-Supervised Feature Matching.

Autoři: Qin, Zikang Feng, Yumin Wu, Gang a další

Zdroj: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 3, p1472, 20p

Témata: HISTORICAL maps, COMPUTER vision, FEATURE extraction, VISUAL fields, TRANSFORMER models, IMAGE registration

TSGDiff: Rethinking Synthetic Time Series Generation from a Pure Graph Perspective

Autoři: Shen, Lifeng Li, Xuyang Long, Lele

Témata: Machine Learning

Relation: http://arxiv.org/abs/2511.12174

Dostupnost: http://arxiv.org/abs/2511.12174

Kairos: Practical Intrusion Detection and Investigation using Whole-system Provenance

Autoři: Cheng, Zijun Lv, Qiujian Liang, Jinyuan a další

Zdroj: 2024 IEEE Symposium on Security and Privacy (SP). :3533-3551

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Cryptography and Security, Cryptography and Security (cs.CR), Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2308.05034

Application of Convolutional Neural Networks in the Problem of Removing Shadows from Photographs

Autoři: A.S. Alekseychuk Yu.D. Mukin

Zdroj: Modelling and Data Analysis. 14:41-51

Témata: 02 engineering and technology, 0210 nano-technology, 01 natural sciences, 0104 chemical sciences