Search Results - Attention based Convolution Autoencoder~

Shared Attention-based Autoencoder with Hierarchical Fusion-based Graph Convolution Network for sEEG SOZ Identification

Authors: Yan, Huachao Guo, Kailing Song, Shiwei et al.

Index Terms: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Signal Processing, Quantitative Biology - Neurons and Cognition, text

URL: http://arxiv.org/abs/2412.12651

Attention Based Convolution Autoencoder for Dimensionality Reduction in Hyperspectral Images

Authors: Biplab Banerjee Shivam Pande

Source: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. :2727-2730

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 15. Life on land

Access URL: https://ieeexplore.ieee.org/document/9553019/
https://dblp.uni-trier.de/db/conf/igarss/igarss2021.html#PandeB21

Sentiment analysis using attention-based convolution autoencoder (SAABCA)

Authors: Sharma, Neha

Subject Terms: Deep Learning, Attention based Convolution Autoencoder, Sentiment Analysis, Autoencoder

A hybrid deep learning-based fruit classification using attention model and convolution autoencoder

Authors: Shifeng Liu Yicao Ma Gang Xue

Source: Complex & Intelligent Systems, Vol 9, Iss 3, Pp 2209-2219 (2020)

Subject Terms: 2. Zero hunger, 03 medical and health sciences, 0302 clinical medicine, CBAM, Electronic computers. Computer science, 0202 electrical engineering, electronic engineering, information engineering, DenseNet, Convolutional neural networks, QA75.5-76.95, Information technology, 02 engineering and technology, T58.5-58.64, Fruit classification

Access URL: https://link.springer.com/content/pdf/10.1007/s40747-020-00192-x.pdf
https://doaj.org/article/f471e943f5404b519098b2e7964c70a7
https://link.springer.com/content/pdf/10.1007/s40747-020-00192-x.pdf
https://link.springer.com/article/10.1007/s40747-020-00192-x

Multiscale Convolution and Attention based Denoising Autoencoder for Motion Artifact Removal in ECG Signals

Authors: Meng Chen Yongjian Li Xiuxin Zhang et al.

Source: Proceedings of the 2024 7th International Conference on Image and Graphics Processing. :442-448

基于特征缩减与自注意力机制的入侵检测方法.

Alternate Title: An intrusion detection method based on feature reduction and self-attention mechanism.

Authors: 金志刚 周峻毅 武晓栋

Source: Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban. Oct2025, Vol. 57 Issue 10, p112-122. 11p.

Subject Terms: Intrusion detection systems (Computer security), Autoencoder, Data structures, Computer network traffic, Computer network security, Feature selection

Hybrid attention convolution acoustic model based on variational autoencoder for speech recognition

Authors: Tang, Haoyu Svendsen, Torbjørn Imram, Ali et al.

Contributors: Tang, Haoyu Svendsen, Torbjørn Imram, Ali et al.

Availability: http://hdl.handle.net/11250/2624676

A mixed‐attention‐based multi‐scale autoencoder algorithm for fabric defect detection

Authors: Hongwei Zhang Yanzi Wu Shuai Lu et al.

Source: Coloration Technology. 140:451-466

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Sentiment Analysis-Based Automatic Stress and Emotion Recognition using Weighted Fused Fusion-Based Cascaded DTCN with Attention Mechanism from EEG Signal.

Authors: Kathole, Atul B. Lonare, Savita Dharmale, Gulbakshee et al.

Source: Journal of Information & Knowledge Management. Oct2024, Vol. 23 Issue 5, p1-37. 37p.

Subject Terms: *Feature extraction, Emotion recognition, Optimization algorithms, Emotions, Brain waves

A hybrid deep learning-based fruit classification using attention model and convolution autoencoder.

Authors: Xue, Gang Liu, Shifeng Ma, Yicao

Source: Complex & Intelligent Systems; Jun2023, Vol. 9 Issue 3, p2209-2219, 11p

Subject Terms: IMAGE recognition (Computer vision), FRUIT

Relative Attention-based One-Class Adversarial Autoencoder for Continuous Authentication of Smartphone Users

Authors: Hu, Mingming Zhang, Kun You, Ruibang et al.

Index Terms: Computer Science - Human-Computer Interaction, text

URL: http://arxiv.org/abs/2210.16819

A novel intelligent fault diagnosis method for gearbox based on multi-dimensional attention denoising convolution.

Authors: Liu W Zhang Z Ye Z et al.

Source: Scientific reports [Sci Rep] 2024 Oct 21; Vol. 14 (1), pp. 24688. Date of Electronic Publication: 2024 Oct 21.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE

SFFHO: Development of Statistical Fitness-based Fire Hawk Optimizer for Software Testing and Maintenance Approach using Adaptive Deep Learning Method.

Authors: Prabu, G. Sujatha, C. Shine, J. Erin et al.

Source: Journal of Electronic Testing. Jun2025, Vol. 41 Issue 3, p313-338. 26p.

Subject Terms: *CONVOLUTIONAL neural networks, *ARTIFICIAL intelligence, *IMAGE processing software, *RECURRENT neural networks, *DEEP learning, *SOFTWARE maintenance, *COMPUTER software testing

Research on residual attention-based mechanism autoencoder for microseismic denoising network model.

Authors: Li, Jiaming Tang, Beichang Zhang, Shuguang et al.

Source: Mechanical Systems & Signal Processing. Oct2025, Vol. 239, pN.PAG-N.PAG. 1p.

Subject Terms: *SIGNAL denoising, *AUTOENCODERS, *SIGNAL-to-noise ratio, *MICROSEISMS, *ARTIFICIAL neural networks, *SIGNAL detection, *SIGNAL processing

Graph attention autoencoder inspired CNN based brain tumor classification using MRI.

Authors: Mishra, Lalita Verma, Shekhar

Source: Neurocomputing. Sep2022, Vol. 503, p236-247. 12p.

Subject Terms: *BRAIN tumors, *TUMOR classification, *PIXELS, *MAGNETIC resonance imaging, *COMPUTER-assisted image analysis (Medicine), *CONVOLUTIONAL neural networks

基于CBDAE 和 TCN-Transformer 的工业传感器时间序列预测.

Alternate Title: Industrial sensor time series prediction based on CBDAE and TCN-Transformer.

Authors: 许涛 南新元 蔡鑫 et al.

Source: Journal of Nanjing University of Information Science & Technology (Natural Science Edition) / Nanjing Xinxi Gongcheng Daxue Xuebao (ziran kexue ban). Jul2025, Vol. 17 Issue 4, p455-466. 12p.

Subject Terms: *Transformer models, Process capability, Autoencoder, Time series analysis, Data scrubbing

HAMC-ID: hybrid attention-based meta-classifier for intrusion detection.

Authors: Antony Joseph Raj S Madiajagan M

Source: Scientific reports [Sci Rep] 2025 Dec 06. Date of Electronic Publication: 2025 Dec 06.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

CAD-IGMS: Cyber attack detection in an intelligent grid management system via the deep learning enhancing grid reliability

Authors: R. Ithaya R. Shobana Ashis Kumar Mishra et al.

Source: Ain Shams Engineering Journal, Vol 16, Iss 12, Pp 103678- (2025)

Subject Terms: Cyber security, Intelligent grid management system, SCADA, Cyberattack detection, Self- attention-based convolution neural network, Engineering (General). Civil engineering (General), TA1-2040

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2090447925004198; https://doaj.org/toc/2090-4479

Access URL: https://doaj.org/article/c1620d9b2b0642219699ae9581b31199

MRI-Based Spinal Condition Classification Using Improved 3DRMAU-Net-DCSE and Ensembled Deep Learning with Optimization Techniques

Authors: Sultan Ahmed Almalki

Source: International Journal of Computational Intelligence Systems, Vol 18, Iss 1, Pp 1-40 (2025)

Subject Terms: MRI-based spinal condition classification, UNet, Deep learning, CNN, Attention mechanism, Hybrid optimization, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://doaj.org/toc/1875-6883

Access URL: https://doaj.org/article/1f47005da1824fd98444ff80e4687e54

A GAI-based multi-scale convolution and attention mechanism model for music emotion recognition and recommendation from physiological data.

Authors: Han, Xiao Chen, Fuyang Ban, Junrong

Source: Applied Soft Computing. Oct2024, Vol. 164, pN.PAG-N.PAG. 1p.

Subject Terms: Generative artificial intelligence, Music & emotions, Galvanic skin response, Emotion recognition, Heart beat, Deep learning