Search Results - Reduced deep convolutional stack autoencoder

Epileptic Seizure Recognition Using Reduced Deep Convolutional Stack Autoencoder and Improved Kernel RVFLN From EEG Signals

Authors: Mrutyunjaya Sahani Susanta Kumar Rout Pradipta Kishor Dash

Source: IEEE Transactions on Biomedical Circuits and Systems. 15:595-605

Subject Terms: Epilepsy, Seizures, 0202 electrical engineering, electronic engineering, information engineering, Humans, Electroencephalography, Signal Processing, Computer-Assisted, Neural Networks, Computer, 02 engineering and technology, Child, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/34156948
https://ieeexplore.ieee.org/document/9462442/
https://europepmc.org/article/MED/34156948

Precise single step and multistep short-term photovoltaic parameters forecasting based on reduced deep convolutional stack autoencoder and minimum variance multikernel random vector functional network

Authors: Mrutyunjaya Sahani Sasmita Choudhury Marif Daula Siddique et al.

Source: Engineering Applications of Artificial Intelligence. 136:108935

Deep Convolutional Stack Autoencoder of Process Adaptive VMD Data With Robust Multikernel RVFLN for Power Quality Events Recognition

Authors: Mrutyunjaya Sahani Pradipta Kishore Dash

Source: IEEE Transactions on Instrumentation and Measurement. 70:1-12

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

Access URL: https://ieeexplore.ieee.org/document/9335941
http://ieeexplore.ieee.org/iel7/19/9259274/09335941.pdf
https://dblp.uni-trier.de/db/journals/tim/tim70.html#SahaniD21

Epileptic Seizure Recognition Using Reduced Deep Convolutional Stack Autoencoder and Improved Kernel RVFLN From EEG Signals.

Authors: Sahani, Mrutyunjaya Rout, Susanta Kumar Dash, Pradipta Kishor

Source: IEEE Transactions on Biomedical Circuits & Systems; Jun2021, Vol. 16 Issue 3, p595-605, 11p

Coupling of a lightweight model of reduced convolutional autoencoder with linear SVM classifier to detect brain tumours on FPGA.

Authors: Chatterjee, Soumita Pandit, Soumya Das, Arpita

Source: Expert Systems with Applications. Sep2025, Vol. 290, pN.PAG-N.PAG. 1p.

Subject Terms: *BRAIN tumors, *SUPPORT vector machines, *MACHINE learning, *PATTERN perception, *FIELD programmable gate arrays, *STATISTICAL models, *PATTERN recognition systems, *AUTOENCODERS

RDCSAE-RKRVFLN: A unified deep learning framework for robust and accurate DOA estimation.

Authors: Raiguru, Priyadarshini Swain, Bhanja Kishor Rout, Susanta Kumar et al.

Source: Applied Soft Computing. Sep2024, Vol. 162, pN.PAG-N.PAG. 1p.

Subject Terms: Convolutional neural networks, Standard deviations, Supervised learning, Direction of arrival estimation, Field programmable gate arrays, Deep learning

FPGA-Based Semisupervised Multifusion RDCNN of Process Robust VMD Data With Online Kernel RVFLN for Power Quality Events Recognition.

Authors: Sahani, Mrutyunjaya Dash, Pradipta Kishore

Source: IEEE Transactions on Neural Networks & Learning Systems; Feb2022, Vol. 33 Issue 2, p515-527, 13p

Subject Terms: CONVOLUTIONAL neural networks, PARTICLE swarm optimization, FIELD programmable gate arrays, FEATURE extraction, MATHEMATICAL optimization

Heart Diseases Prediction Using Deep Convolutional Neural Network with Deformable Angular Alignment Module.

Authors: Kumar, Voruganti Naresh Ramatenki, Sateesh Kumar Marri, Sireesha et al.

Source: International Journal of Intelligent Engineering & Systems; 2025, Vol. 18 Issue 11, p551-565, 15p

Subject Terms: HEART diseases, CONVOLUTIONAL neural networks, PREDICTIVE validity, COMPUTER-assisted image analysis (Medicine), FEATURE extraction, DEEP learning, ELECTROCARDIOGRAPHY

Deep Convolutional Neural Networks Provide Motion Grading for High-Resolution Peripheral Quantitative Computed Tomography of the Scaphoid.

Authors: Benedikt, Stefan Zelger, Philipp Horling, Lukas et al.

Source: Diagnostics (2075-4418); Mar2024, Vol. 14 Issue 5, p568, 11p

Subject Terms: CONVOLUTIONAL neural networks, COMPUTED tomography, DEEP learning, ARTIFICIAL intelligence

Deep Convolutional Neural Networks for Plant Disease Detection: A Mobile Application Approach (Agri Bot).

Authors: Ibrahim, Hegazi Ahmed, Abdelmoty M. Bouallegue, Belgacem et al.

Source: International Journal of Intelligent Systems; 5/30/2025, Vol. 2025, p1-19, 19p

Subject Terms: CONVOLUTIONAL neural networks, PLANT diseases, AGRICULTURE, AUTOENCODERS, CROP yields

Deep Medical Image Reconstruction with Autoencoders using Deep Boltzmann Machine Training.

Authors: S., Saravanan Juliet, Sujitha

Source: EAI Endorsed Transactions on Pervasive Health & Technology; 2020, Vol. 6 Issue 24, p1-9, 9p

Subject Terms: MACHINE learning, LOGISTIC regression analysis, STAKEHOLDERS, COMPARATIVE studies, ELECTRONIC health records

Inpainting non-anatomical objects in brain imaging using enhanced deep convolutional autoencoder network.

Authors: Kumar, Puranam Revanth Shilpa, B Jha, Rajesh Kumar et al.

Source: Sādhanā: Academy Proceedings in Engineering Sciences; Jun2024, Vol. 49 Issue 2, p1-13, 13p

Deep‐Learning‐Based Adjoint State Method: Methodology and Preliminary Application to Inverse Modeling.

Authors: Xiao, Cong Deng, Ya Wang, Guangdong

Source: Water Resources Research; Feb2021, Vol. 57 Issue 2, p1-20, 20p

Subject Terms: CONVOLUTIONAL neural networks, PARAMETER estimation, DEEP learning, TWO-dimensional models

Accident Impact Prediction Based on a Deep Convolutional and Recurrent Neural Network Model.

Authors: Sajadi, Pouyan Qorbani, Mahya Moosavi, Sobhan et al.

Source: Urban Science; Aug2025, Vol. 9 Issue 8, p299, 30p

Subject Terms: TRAFFIC accidents, PREDICTION models, DEEP learning, REAL-time computing, TRAFFIC safety, CONVOLUTIONAL neural networks, LONG short-term memory

Geographic Terms: LOS Angeles County (Calif.)

Skin Lesion Synthesis and Classification Using an Improved DCGAN Classifier.

Authors: Behara, Kavita Bhero, Ernest Agee, John Terhile

Source: Diagnostics (2075-4418); Aug2023, Vol. 13 Issue 16, p2635, 29p

Subject Terms: GENERATIVE adversarial networks, DEEP learning, CONVOLUTIONAL neural networks, DATA augmentation, SKIN imaging

Parkinson's disease Severity Detection Based on Fused features with tuned Residual Deep Convolutional Neural Network.

Authors: Vishwakarma, Gagan Nandanwar, Amit Kumar Thakur, Ghanshyam Singh

Source: Multimedia Tools & Applications; Apr2025, Vol. 84 Issue 14, p13111-13131, 21p

Subject Terms: CONVOLUTIONAL neural networks, PARKINSON'S disease, ARTIFICIAL intelligence, FEATURE extraction, OPTIMIZATION algorithms

Real-time facial emotion recognition model based on kernel autoencoder and convolutional neural network for autism children.

Authors: Talaat, Fatma M. Ali, Zainab H. Mostafa, Reham R. et al.

Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications; May2024, Vol. 28 Issue 9/10, p6695-6708, 14p

Subject Terms: EMOTION recognition, CONVOLUTIONAL neural networks, AUTISM in children, AUTISTIC children, MACHINE learning, DEEP learning, ASSISTIVE technology, FACIAL muscles

NRDPU-Net: A Normalized Residual Depth U-Net with Ridge Vessel Preprocessing for Accurate Melanoma Classification

Authors: Shyamala Devi, M Natarajan, Yuvaraj K. R., Sri Preethaa

An Efficient Mutual Authentication and Fractional Lyrebird Optimization With Deep Learning–Based SIP‐Based DRDoS Attack Detection.

Authors: Sreenivasulu, V. Ravikumar, C. V. Poruran, Sivakumar

Source: International Journal of Distributed Sensor Networks; 8/7/2025, Vol. 2025, p1-24, 24p

Subject Terms: DEEP learning, DENIAL of service attacks, INTRUSION detection systems (Computer security), SECURITY management, ELECTRONIC authentication, OPTIMIZATION algorithms, SESSION Initiation Protocol (Computer network protocol)

Impact of Patch-Size on Classification Accuracy of Latent Fingerprint Image in Stacked Convolutional Auto-encoder based Segmentation and Detection

Authors: Manoj Kumar Shukla Megha Chhabra Kiran Kumar Ravulakollu

Source: 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :367-372

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 16. Peace & justice

Access URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9243356
http://xplorestaging.ieee.org/ielx7/9243168/9243301/09243356.pdf?arnumber=9243356