Výsledky vyhledávání - sparse conventional autoencoder ((((same OR sae) OR sage) OR cae))

An Explainable AI Framework Integrating Variational Sparse Autoencoder and Random Forest for EEG-Based Epilepsy Detection

Autoři: Pratiti Mishra Himansu Das

Zdroj: IEEE Access, Vol 13, Pp 179568-179583 (2025)

Témata: EEG, epilepsy, LIME, RF, SAE, SHAP, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11202459/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/5ce5fe264c50481f8759c3ca8ec138c9

Sensor-Driven Surrogate Modeling and Control of Nonlinear Dynamical Systems Using FAE-CAE-LSTM and Deep Reinforcement Learning

Autoři: Kherad, M. Moayyedi, M. K. Fotouhi-Ghazvini, F. a další

Zdroj: Sensors. 25(16)

Témata: Autoencoders, Control Of Dynamical Systems, Cyber-physical Systems, Deep Reinforcement Learning, Long Short-term Memory, Sensor-driven Modeling, Circular Cylinders, Computer Control Systems, Convolution, Dynamical Systems, Dynamics, Embedded Systems, Flow Control, Fuel Additives, Nonlinear Dynamical Systems, Real Time Control, Robust Control, Auto Encoders, Control Of Dynamical System, Cybe-physical Systems, High-dimensional, Higher-dimensional, Reinforcement Learning Agent, Reinforcement Learnings, Short Term Memory

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-73172
https://doi.org/10.3390/s25165149

A Trustworthy Artificial Intelligence Framework for Predicting Gasoline Octane Loss Using Sparse Autoencoder and Stacking Ensemble Learning in Petrochemical Processes

Autoři: Xiaochun Lin Shitao Yin Xiang Li

Investigating Beta-Variational Convolutional Autoencoders for the Unsupervised Classification of Chest Pneumonia.

Autoři: Akila, Serag Mohamed Imanov, Elbrus Almezhghwi, Khaled

Zdroj: Diagnostics (2075-4418); Jul2023, Vol. 13 Issue 13, p2199, 14p

Témata: MACHINE learning, PNEUMONIA, ANOMALY detection (Computer security), LUNG infections, DIAGNOSIS, KLEBSIELLA infections

Efficient sparse-view medical image classification for low radiation and rapid COVID-19 diagnosis.

Autoři: Gwak, Seunghyun Yang, Sooyoung Jeong, Heawon a další

Zdroj: Biomedical Engineering Letters; Jul2025, Vol. 15 Issue 4, p785-795, 11p

Beyond Input Activations: Identifying Influential Latents by Gradient Sparse Autoencoders

Autoři: Shu, Dong Wu, Xuansheng Zhao, Haiyan a další

Témata: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Computation and Language, Computation and Language (cs.CL), Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2505.08080

Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone

Autoři: Bărbălau, Antonio Păduraru, Cristian Daniel Poncu, Teodor a další

Témata: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2509.10809

Resurrecting the Salmon: Rethinking Mechanistic Interpretability with Domain-Specific Sparse Autoencoders

Autoři: O'Neill, Charles Jayasekara, Mudith Kirkby, Max

Témata: Machine Learning, FOS: Computer and information sciences, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2508.09363

Train One Sparse Autoencoder Across Multiple Sparsity Budgets to Preserve Interpretability and Accuracy

Autoři: Balagansky, Nikita Aksenov, Yaroslav Laptev, Daniil a další

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2505.24473

CoCoChain: A Concept-Aware Consensus Protocol for Secure Sensor Data Exchange in Vehicular Ad Hoc Networks.

Autoři: Juárez, Rubén Nicolas-Sans, Ruben Tamames, José Fernández

Zdroj: Sensors (14248220). Oct2025, Vol. 25 Issue 19, p6226. 51p.

Témata: *VEHICULAR ad hoc networks, *BLOCKCHAINS, *MOBILE communication systems, *DATA transmission systems, *DATA integrity, *AUTOENCODERS

A Novel Deep Neural Network-Based Framework for Subsurface Analysis in Non-Stationary Thermal Wave Imaging.

Autoři: Swapna, M. N. Suman, M. Prasanthi, Y. N. a další

Zdroj: Sensing & Imaging; 9/5/2025, Vol. 26 Issue 1, p1-18, 18p

AACNet: attention aided CNN-autoencoder network for precise categorization of respiratory conditions from HRCT scans.

Autoři: Kakati, Anchita Bhattacharjya, Upasana Medhi, Jyoti Prakash a další

Zdroj: Network Modeling & Analysis in Health Informatics & Bioinformatics; 8/20/2025, Vol. 14 Issue 1, p1-29, 29p

Visual Exploration of Feature Relationships in Sparse Autoencoders with Curated Concepts

Autoři: Yan, Xinyuan Liu, Shusen Thopalli, Kowshik a další

Témata: Computation and Language, Machine Learning

Relation: http://arxiv.org/abs/2511.06048

Dostupnost: http://arxiv.org/abs/2511.06048

Hybrid Deep Learning Models for Analyzing Histological Images of the Zebrafish Intestine Under Oxidative Stress.

Autoři: Pavel, Cristian Dan Moldovanu, Simona Pavel, Irina Andreea a další

Zdroj: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 22, p2859, 16p

Témata: OXIDATIVE stress, CONVOLUTIONAL neural networks, ZEBRA danio, DEEP learning, IMAGE enhancement (Imaging systems), ARTIFICIAL intelligence, HISTOPATHOLOGY, CLASSIFICATION

Comparing Functional and Effective Connectivity Features in Diagnosis of Autism Spectrum Disorder Using Stacked Autoencoder by Resting-State fMRI Data.

Autoři: Navaei, Pegah Khadem, Ali Zaferani, Effat Jalaeian

Zdroj: Frontiers in Biomedical Technologies; Autumn2025, Vol. 12 Issue 4, p830-843, 14p

Témata: AUTISM spectrum disorders, FUNCTIONAL connectivity, AUTOENCODERS, ARTIFICIAL neural networks, FUNCTIONAL magnetic resonance imaging, GRANGER causality test

DEEP LEARNING-BASED FACE-IRIS RECOGNITION WITH CAPSULE NEURAL NETWORK (CAPSNET) FOR BIOMETRIC ATTENDANCE SYSTEM.

Autoři: KARUNAKARAN, SANGEETHA AKILA, A.

Zdroj: TPM: Testing, Psychometrics, Methodology in Applied Psychology; 2025 Supplement, Vol. 32, p345-358, 14p

Interpretable Reward Model via Sparse Autoencoder

Autoři: Zhang, Shuyi Shi, Wei Li, Sihang a další

Témata: Machine Learning, FOS: Computer and information sciences, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2508.08746

Comprehensive review of machine learning and deep learning techniques for epileptic seizure detection and prediction based on neuroimaging modalities.

Autoři: Slama, Khadija Yahyaouy, Ali Riffi, Jamal a další

Zdroj: Visual Computing for Industry, Biomedicine & Art; 12/11/2025, Vol. 8 Issue 1, p1-37, 37p

HDMcCNet: A Hybrid Deep Multi-label Classification Network for Diagnosing Multiple Ocular Disease via Fundus Images.

Autoři: Merlin, R. Vincy Lloyd, F.

Zdroj: Sensing & Imaging; 12/8/2025, Vol. 26 Issue 1, p1-49, 49p

Hybrid graph-based models in medical decision support.

Autoři: Bouslimi, Riadh Zitouni, Fatma Ben Smida, Takwa a další

Zdroj: Network Modeling & Analysis in Health Informatics & Bioinformatics; 12/4/2025, Vol. 14 Issue 1, p1-21, 21p