Non-iterative and Fast Deep Learning: Multilayer Extreme Learning Machines

Deep Residual Learning for Image Recognition

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Modified online sequential extreme learning machine algorithm using model predictive control approach

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A modified projective forward-backward splitting algorithm for variational inclusion problems to predict Parkinson's disease

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Efficient parameter tuning of neural foundation models for drug perspective prediction from unstructured socio-medical data

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Intelligent fault diagnosis of rolling bearing based on time–frequency processing and DLKA-YOLO

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Hybrid Grey Wolf Optimization-Based Gaussian Process Regression Model for Simulating Deterioration Behavior of Highway Tunnel Components

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( Q , S , R ) - γ -dissipative control of T-S fuzzy systems via aperiodic sampling control with communication delay

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A hybrid optimization method by incorporating adaptive response strategy for Feedforward neural network

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TSTELM: Two-Stage Transfer Extreme Learning Machine for Unsupervised Domain Adaptation

Zang, S., Li, X., Ma, J., Yan, Y., Gao, J., & Wei, Y. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/1582624 · Cited by 8

Model-agnostic meta-learning-based region-adaptive parameter adjustment scheme for influenza forecasting

Moon, J., Noh, Y., Park, S., & Hwang, E. (2022) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2022.11.009 · Cited by 8

A Convolutional Neural Network for Beamforming and Image Reconstruction in Passive Cavitation Imaging

Sharahi, H. J., Acconcia, C. N., Li, M., Martel, A. L., & Hynynen, K. (2023) · Sensors · doi:10.3390/s23218760 · Cited by 8

Assessing urban river landscape visual quality with extreme learning machines: A case study of the yellow river in ningxia hui autonomous region, china

Ji, G., & Sun, H. (2024) · Ecological Indicators · doi:10.1016/j.ecolind.2024.112173 · Cited by 8

Detecting Rotational Symmetry in Polar Domain Based on SIFT

Akbar, H., Iqbal, M. M., Ali, A., Parveen, A., Samee, N. M. A., Alohali, M. A., & Muthanna, M. S. A. (2023) · IEEE Access · doi:10.1109/access.2023.3282890 · Cited by 7

An automatic Darknet-based immunohistochemical scoring system for IL-24 in lung cancer

He, Z., Jia, D., Zhang, C., Li, Z., & Wu, N. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.107485 · Cited by 7

Deep and wide nonnegative matrix factorization with embedded regularization

Moayed, H., & Mansoori, E. G. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110530 · Cited by 8

Approximation Properties of Ridge Functions and Extreme Learning Machines

Jørgensen, P. E. T., & Stewart, D. E. (2021) · SIAM Journal on Mathematics of Data Science · doi:10.1137/20m1356348 · Cited by 7

Multilayer extreme learning machine-based unsupervised deep feature representation for heartbeat classification

Xu, Y., Liu, L., Zhang, S., & Xiao, W. (2023) · Soft Computing · doi:10.1007/s00500-023-07861-2 · Cited by 7

A time efficient offline handwritten character recognition using convolutional extreme learning machine

Dey, R., Piri, J., Behera, D. K., & Khan, A. U. (2023) · The Imaging Science Journal · doi:10.1080/13682199.2023.2223011 · Cited by 7

Distributional reinforcement learning with unconstrained monotonic neural networks

Théate, T., Wehenkel, A., Bolland, A., Louppe, G., & Ernst, D. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.02.049 · Cited by 6

Improved design and analysis of MPPT technique for photovoltaic power systems to increase accuracy and speed under different conditions

Hai, T., Rezvani, A., & Le, B. N. (2023) · Environment Development and Sustainability · doi:10.1007/s10668-023-03116-0 · Cited by 6

Building Automation Pipeline for Diagnostic Classification of Sporadic Odontogenic Keratocysts and Non-Keratocysts Using Whole-Slide Images

Mohanty, S., Shivanna, D. B., Rao, R. S., Astekar, M. S., Chandrashekar, C., Radhakrishnan, R. A., Sanjeevareddygari, S., Kotrashetti, V., & Kumar, P. (2023) · Diagnostics · doi:10.3390/diagnostics13213384 · Cited by 5

ReLP: Reinforcement Learning Pruning Method Based on Prior Knowledge

Zhang, W., Ji, M., Yu, H., & Zhen, C. (2022) · Neural Processing Letters · doi:10.1007/s11063-022-11058-3 · Cited by 5

Application of DQN-IRL Framework in Doudizhu’s Sparse Reward

Kong, Y., Shi, H., Wu, X., & Rui, Y. (2023) · Neural Processing Letters · doi:10.1007/s11063-023-11209-0 · Cited by 6

A Robust Extreme Learning Machine Based on Adaptive Loss Function for Regression Modeling

Zhang, F., Chen, S., Hong, Z., Shan, B., & Xu, Q. (2023) · Neural Processing Letters · doi:10.1007/s11063-023-11340-y · Cited by 5

DySuse: Susceptibility estimation in dynamic social networks

Shi, Y., Zhou, J., & Zhang, C. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121042 · Cited by 5

Target adaptive extreme learning machine for transfer learning

Ri, J. H., Kang, T. G., & Choe, C. R. (2023) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-023-01947-x · Cited by 5

An intelligent algorithm of amyloid plucks to timely fault-predicting and contending dependability in IoMT

Rahmani, A. M., & Mirmahaleh, S. Y. H. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122068 · Cited by 5

Recursive Router Metrics Prediction Using Machine Learning-Based Node Modeling for Network Digital Replica

Hattori, K., Korikawa, T., Takasaki, C., & Oowada, H. (2023) · IEEE Access · doi:10.1109/access.2023.3340696 · Cited by 5

Is There a New Road to Spinal Cord Injury Rehabilitation? A Case Report about the Effects of Driving a Go-Kart on Muscle Spasticity

Farì, G., Ranieri, M., Marvulli, R., Dell’Anna, L., Fai, A., Tognolo, L., Bernetti, A., Caforio, L., Megna, M., & Losavio, E. (2023) · Diseases · doi:10.3390/diseases11030107 · Cited by 5

Computationally efficient neural hybrid automaton framework for learning complex dynamics

Wang, T., Yang, Y., & Xiang, W. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126879 · Cited by 5

NER Sequence Embedding of Unified Medical Corpora to Incorporate Semantic Intelligence in Big Data Healthcare DiagnosticsPreprint

Shafqat, S., Anwar, Z., Javaid, Q., & Ahmad, H. F. (2023) · Qeios · doi:10.32388/hpauyj · Cited by 5

TfELM: Extreme Learning Machines framework with Python and TensorFlow

Struniawski, K., & Kozera, R. (2024) · SoftwareX · doi:10.1016/j.softx.2024.101833 · Cited by 5

Penetration Overload Prediction Method Based on a Deep Neural Network with Multiple Inputs

Ma, H., Sun, H., & Li, C. (2023) · Applied Sciences · doi:10.3390/app13042351 · Cited by 4

Online Learning-Based Adaptive Device-Free Localization in Time-Varying Indoor Environment

Xue, J., Chen, X., Chi, Q., & Xiao, W. (2024) · Applied Sciences · doi:10.3390/app14020643 · Cited by 5

Domain Adaptation Based on Semi-Supervised Cross-Domain Mean Discriminative Analysis and Kernel Transfer Extreme Learning Machine

Li, X., & Ma, J. (2023) · Sensors · doi:10.3390/s23136102 · Cited by 4

An Inferential Commonsense-Driven Framework for Predicting Political Bias in News Headlines

Swati, S., Mladenić, D., & Grobelnik, M. (2023) · IEEE Access · doi:10.1109/access.2023.3298877 · Cited by 5

Automatic DNN architecture design using CPSOTJUTT for power system inspection

Lv, X., Chiang, H., & Dong, N. (2023) · Journal Of Big Data · doi:10.1186/s40537-023-00828-y · Cited by 4

Improving top- N recommendations using batch approximation for weighted pair-wise loss

Aftab, S., & Ramampiaro, H. (2023) · Machine Learning with Applications · doi:10.1016/j.mlwa.2023.100520 · Cited by 4

A Petri Net and LSTM Hybrid Approach for Intrusion Detection Systems in Enterprise Networks

Volpe, G., Fiore, M., la Grasta, A., Albano, F., Stefanizzi, S., Mongiello, M., & Mangini, A. M. (2024) · Sensors · doi:10.3390/s24247924 · Cited by 6

Multivariate Extreme Learning Machine Based AutoEncoder for Electricity Consumption Series Clustering

Zheng, K., Yang, J., Gong, Q., Zhou, S., Zeng, L., & Li, S. (2021) · IEEE Access · doi:10.1109/access.2021.3124009 · Cited by 4

Stereoscopic Image Quality Evaluation Method for Visual Communication Design

Han, X., Shan, Q., & Chu, T. (2023) · IEEE Access · doi:10.1109/access.2023.3334154 · Cited by 4

Investigating the Terrain of Class-Incremental Continual Learning: A Brief Survey

Nokhwal, S., Kumar, N., & Shiva, S. G. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-97-7426-5_25 · Cited by 4

Artificial intelligence and its performance impacts in the oil and gas industry: Challenges, insights, and evaluation approaches

AlAbdouli, M. A., & Al‐Shihabi, S. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.107636 · Cited by 7

BDBRC: A Chinese military entity recognition model combining context contribution and residual dilatation convolutional networks

Wang, J., Qu, J., Zhao, Z., & Yin, Y. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101799 · Cited by 3

A Comparison Study About Parameter Optimization Using Swarm Algorithms

Carvalho, H. D. P. D., Soares, W. L., Santos, W. B., & Fagundes, R. (2022) · IEEE Access · doi:10.1109/access.2022.3175202 · Cited by 3

Graph learning considering dynamic structure and random structure

Dong, H., Ma, H., Du, Z., Zhou, Z., Yang, H., & Wang, Z. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101633 · Cited by 3

A Novel Non-iterative Training Method for CNN Classifiers Using Gram–Schmidt Process

Azam, B., Kuttichira, D. P., Sanjeewani, P., Verma, B., Rahman, A., & Wang, L. (2025) · Neural Processing Letters · doi:10.1007/s11063-025-11741-1 · Cited by 3

Research on multi-task collaborative enhancement matrix machine and its application in fault diagnosis

Chen, C., Pan, H., Zheng, J., Tong, J., & Cheng, J. (2025) · Measurement Science and Technology · doi:10.1088/1361-6501/adba7e · Cited by 3

Smart Waste Revolution: AI-Powered Biomedical Segregation and Recycling with IoT Integration

Uthayakumar, G., Sankaranarayanan, B., & Bhalaji, R. K. A. (2024) · International Journal of Mechanical Engineering · doi:10.14445/23488360/ijme-v11i12p104 · Cited by 2

Expectation-Maximization via Pretext-Invariant Representations

Oinar, C., Le, B. M., & Woo, S. S. (2023) · IEEE Access · doi:10.1109/access.2023.3289589 · Cited by 2

ELM-Based Discriminant Auto-Encoder and Multi-Kernel Fusion for Radar Specific Emitter Identification

Shi, Y. K., Wang, C., Ge, G., Liu, F., & Zhang, L. (2023) · IEEE Access · doi:10.1109/access.2023.3322375 · Cited by 2

Robust finite frequency control for MRF damper-based semi-active suspension systems subject to time delay and hysteresis nonlinearity

Deng, M., Wong, P. K., Gao, Z., Ma, X., & Zhao, J. B. (2024) · Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · doi:10.1177/09596518241262502 · Cited by 2

Deep Learning in Biometric Recognition: Applications and Challenges

Jiang, Z., Li, H., Sui, X., Cai, Y., Yu, G., & Zhang, W. (2024) · IEEE International Conference on Sensors, Electronics and Computer Engineering (ICSECE) · doi:10.1109/icsece61636.2024.10729252 · Cited by 2

Increasing the accuracy of an extreme learning machine using a chaos particle swarm optimization algorithm

Rasa, G. R. R., Mood, S. E., & Abbasi, E. (2025) · Evolving Systems · doi:10.1007/s12530-025-09763-0 · Cited by 2

Online Sequential Complex-Valued ELM for Noncircular Signals: Augmented Structures and Learning Algorithms

Wang, H., Wang, Y., Zhu, S., & Zhang, H. (2021) · IEEE Access · doi:10.1109/access.2021.3076345 · Cited by 2

A GPU-based accelerated ELM and deep-ELM training algorithms for traditional and deep neural networks classifiers

Chegni, A. M., Ghavami, B., & Eftekhari, M. (2022) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2022.200098 · Cited by 2

Detecting Movement Changes in Children with Hemiparesis after Upper Limb Therapies: A Responsiveness Analysis of a 3D Bimanual Protocol

Cacioppo, M., Lempereur, M., Houx, L., Bouvier, S., Bailly, R., & Brochard, S. (2023) · Sensors · doi:10.3390/s23094235 · Cited by 2

Outlier detection toward high-dimensional industrial data using extreme tensor-train learning machine with compression

Deng, X., Shi, Y., & Yao, D. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101576 · Cited by 1

Axial Constraints for Global Matching-Based Optical Flow Estimation

Kim, E., Jun, W., & Heo, J. (2023) · IEEE Access · doi:10.1109/access.2023.3290993 · Cited by 1

Quantitative analysis of safflower seed oil adulteration based on near-infrared spectroscopy combined with improved sparrow algorithm optimization model ISSA-ELM

Xu, S., Yan-dong, Z., Lu-shuai, Q., Kai-xing, H., & Fu, Y. (2025) · Analytical Methods · doi:10.1039/d4ay02252a · Cited by 1

تأثير تطبيق الذكاء الاصطناعي في تحقيق الريادة الاستراتيجية: دراسة وصفية تحليلية لآراء عينة من الموظفين في الشركة العامة لصناعة الزجاج والسيراميك والحراريات في الرمادي

ابراهيم, م. ف. (2024) · Tikrit Journal of Administrative and Economic Sciences · doi:10.25130/tjaes.20.68.2.1 · Cited by 1

Coal origin identification based on visible-infrared spectroscopy and attention networks

Liu, J., Le, B. T., & Ha, T. T. L. (2025) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2025.105501 · Cited by 1

Optimization of Feature Weighting for Epitope Classification in B-Cell and SARS Using TVIWACRI-PSO-ELM

Cholissodin, I., Suciati, N., Herumurti, D., Sarno, R., & Yurina, V. (2023) · International Conference on Information & Communication Technology and System (ICTS) · doi:10.1109/icts58770.2023.10330844 · Cited by 1

NER Sequence Embedding of Unified Medical Corpora to Incorporate Semantic Intelligence in Big Data Healthcare DiagnosticsPreprint

Shafqat, S., Anwar, Z., Javaid, Q., & Ahmad, H. F. (2024) · Research Square · doi:10.21203/rs.3.rs-3148503/v2 · Cited by 1

Artificial Intelligence & its Performance Impacts in the Oil & Gas Industry: Challenges, Insights, and Evaluation ApproachesPreprint

AlAbdouli, M. A., & Al‐Shihabi, S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5215422 · Cited by 1

Convergence analysis on the deterministic mini-batch learning algorithm for noise resilient radial basis function networks

Wong, H. T., Leung, C.-S., & Kwong, S. (2022) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-022-01550-6

Using AI to detect and classify malicious domain names

Priya, S. B., Reddy, V., & Balaji, V. (2022) · International Journal of Health Sciences · doi:10.53730/ijhs.v6ns1.7198

A deep semi-dense compression network for reinforcement learning based on information theory

Wen, J., Xi, M., Xiao, T., Yang, J., Chen, D., Lu, W. B., & Gao, X. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.02.001

NER Sequence Embedding of Unified Medical Corpora to incorporate Semantic Intelligence in Big Data Healthcare DiagnosticsPreprint

Shafqat, S., Anwar, Z., Javaid, Q., & Ahmad, H. F. (2023) · Research Square · doi:10.21203/rs.3.rs-3148503/v1

NER Sequence Embedding of Unified Medical Corpora to Incorporate Semantic Intelligence in Big Data Healthcare DiagnosticsPreprint

Shafqat, S., Anwar, Z., Javaid, Q., & Ahmad, H. F. (2024) · Qeios · doi:10.32388/hpauyj.2

Design of Intelligent Network English Automatic Scoring Algorithm Based on CS-ELM

Jin, Y. (2024) · International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS) · doi:10.1109/aiars63200.2024.00079

Constraints on typical relic gravitational waves based on data of LIGO

Zhang, M., & Wen, H. (2025) · Communications in Theoretical Physics · doi:10.1088/1572-9494/adb5f5

Optimizing CNNs with Gram Schmidt Non-iterative Learning for Image Recognition

Kuttichira, D. P., Azam, B., Verma, B., Rahman, A., & Wang, L. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-6582-2_2

Coupler yaw angle identification of heavy-haul locomotives: A multi-scale feature fusion-based method

Xie, R., Chen, S., Song, P., Li, L., Wang, K., & Zhai, W. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.113519

A novel instance segmentation framework for accurate counting of slender and dense objects

Chen, X., Chen, Y., Zhang, Q., Yuan, W., 吕, G. L., & Ren, Y. (2026) · Measurement Science and Technology · doi:10.1088/1361-6501/ae58cb

Power Supply Chain Security Risk Early Warning Based on Self-Adaptive Convergence Factor Matrix-Iterative Extreme Learning Machine

Hongzhi, S., Zhao, J., Lingxiao, C., Jiamian, W., & Shengping, Y. (2026) · Communications in computer and information science · doi:10.1007/978-981-95-6736-2_20

Revolutionizing women’s coronary artery disease prediction in the digital landscape: a comparative study of cutting-edge deep learning and machine learning techniques

Miao, X., Chen, H., Ghorbani, H., Zhu, L., Liu, S., Hovhannisyan, H. S., Zheng, X., & Sun, J. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110437

A hybrid prognostic approach for extra-large-scale bearing using enhanced CERLMDAN-KPCA and MLKELM-AE

Pan, Y., Qin, P., Liu, L., & Liu, Y. (2026) · Journal of Vibration and Control · doi:10.1177/10775463261455831

Software design phase risk estimation using extreme learning machine

Khan, T., Islam, M., & Khan, W. (2026) · Discover Applied Sciences · doi:10.1007/s42452-026-09258-w

Triboelectric nanogenerator based on ZIF-8/ZIF-67/CF composites for self-powered HCHO sensing and indoor environmental monitoring

Luo, N., Zhang, X., Zhu, L., Yin, Y., Wu, J., Li, T., & Liu, C. (2026) · Chemical Engineering Journal · doi:10.1016/j.cej.2026.182235

International GIS Dictionary

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Recent Trends in ELM and MLELM: A review

Parkavi, R. M., Parkavi, R. M., Shanthi, M., & Bhuvaneswari, M. C. (2017) · Advances in Science Technology and Engineering Systems Journal · doi:10.25046/aj020108 · Cited by 8

Multilayer extreme learning machine: a systematic review

Kaur, R., Roul, R. K., & Batra, S. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-14634-4 · Cited by 26

Deep Representation Based on Multilayer Extreme Learning Machine

Qi, Y., & Li, Y. (2016) · Lecture notes in electrical engineering · doi:10.1007/978-981-10-0740-8_17 · Cited by 1

A Review of multilayer extreme learning machine neural networks

Vásquez-Coronel, J. A., Mora, M., & Vilches-Ponce, K. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10478-4 · Cited by 39