Neural Networks and Deep Learning

MISSING-VALUE

(n.d.)

Edge Machine Learning for AI-Enabled IoT Devices: A Review

Merenda, M., Porcaro, C., & Iero, D. (2020) · Sensors · doi:10.3390/s20092533 · Cited by 523 · see citing works

Review of Wearable Devices and Data Collection Considerations for Connected Health

Vijayan, V., Connolly, J. P., Condell, J., McKelvey, N., & Gardiner, P. (2021) · Sensors · doi:10.3390/s21165589 · Cited by 435 · see citing works

Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects

Serradilla, O., Zugasti, E., Rodriguez, J., & Zurutuza, U. (2022) · Applied Intelligence · doi:10.1007/s10489-021-03004-y · Cited by 304 · see citing works

Federated Learning for UAVs-Enabled Wireless Networks: Use Cases, Challenges, and Open Problems

Brik, B., Ksentini, A., & Bouaziz, M. (2020) · IEEE Access · doi:10.1109/access.2020.2981430 · Cited by 258 · see citing works

Applications of Artificial Neural Networks in Greenhouse Technology and Overview for Smart Agriculture Development

Escamilla-García, A., Soto-Zarazúa, G. M., Toledano‐Ayala, M., Rivas-Araiza, E. A., & Gastélum-Barrios, A. (2020) · Applied Sciences · doi:10.3390/app10113835 · Cited by 183 · see citing works

A systematic literature review of deep learning neural network for time series air quality forecasting

Zaini, N., Ean, L. W., Ahmed, A. N., & Malek, M. B. A. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-17442-1 · Cited by 139 · see citing works

Deep Learning and Machine Learning with Grid Search to Predict Later Occurrence of Breast Cancer Metastasis Using Clinical Data

Jiang, X., & Xu, C. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11195772 · Cited by 120 · see citing works

COVID-19 detection in X-ray images using convolutional neural networks

Arias-Garzón, D., Alzate-Grisales, J. A., Orozco-Arias, S., Arteaga-Arteaga, H. B., Bravo-Ortíz, M. A., Mora-Rubio, A., Saborit-Torres, J. M., Montell-Serrano, J. Á., de la Iglesia-Vayá, M., Cardona-Morales, O., et al. (2021) · Machine Learning with Applications · doi:10.1016/j.mlwa.2021.100138 · Cited by 102 · see citing works

PM2.5 forecasting for an urban area based on deep learning and decomposition method

Zaini, N., Ean, L. W., Ahmed, A. N., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-21769-1 · Cited by 89 · see citing works

A review of deep learning and machine learning techniques for hydrological inflow forecasting

Latif, S. D., & Ahmed, A. N. (2023) · Environment Development and Sustainability · doi:10.1007/s10668-023-03131-1 · Cited by 74 · see citing works

Computation offloading in Edge Computing environments using Artificial Intelligence techniques

Carvalho, G., Cabral, B., Pereira, V., & Bernardino, J. (2020) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2020.103840 · Cited by 69 · see citing works

Prediction Skill of Extended Range 2-m Maximum Air Temperature Probabilistic Forecasts Using Machine Learning Post-Processing Methods

Peng, T., Zhi, X., Ji, Y., Ji, L., & Tian, Y. (2020) · Atmosphere · doi:10.3390/atmos11080823 · Cited by 66 · see citing works

Through-Wall Human Pose Reconstruction via UWB MIMO Radar and 3D CNN

Song, Y., Jin, T., Dai, Y., Song, Y., & Zhou, X. (2021) · Remote Sensing · doi:10.3390/rs13020241 · Cited by 68 · see citing works

An artificial neural network model for predicting the performance of thermoacoustic refrigerators

Alamir, M. A. (2020) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2020.120551 · Cited by 48 · see citing works

Predicting Slowdowns in Decadal Climate Warming Trends With Explainable Neural Networks

Labe, Z. M., & Barnes, E. A. (2022) · Geophysical Research Letters · doi:10.1029/2022gl098173 · Cited by 36 · see citing works

The Impact of Local Attention in LSTM for Abstractive Text Summarization

Hanunggul, P. M., & Suyanto, S. (2019) · International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) · doi:10.1109/isriti48646.2019.9034616 · Cited by 33 · see citing works

Comparison of Climate Model Large Ensembles With Observations in the Arctic Using Simple Neural Networks

Labe, Z. M., & Barnes, E. A. (2022) · Earth and Space Science · doi:10.1029/2022ea002348 · Cited by 31 · see citing works

Applications of Deep Learning in Healthcare and Biomedicine

Mittal, S., & Hasija, Y. (2019) · Studies in big data · doi:10.1007/978-3-030-33966-1_4 · Cited by 33 · see citing works

Performance investigation of fire protection and intervention strategies: Artificial neural network-based assessment framework

Ouache, R., Nahiduzzaman, K. M., Hewage, K., et al. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.102439 · Cited by 29 · see citing works

Geometric morphometrics and machine learning as tools for the identification of sibling mosquito species of the Maculipennis complex (Anopheles)

Bellin, N., Calzolari, M., Callegari, E., Bonilauri, P., Grisendi, A., Dottori, M., & Rossi, V. (2021) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2021.105034 · Cited by 29 · see citing works

Deep learning algorithms applied to computational chemistry

Pando, A. G., Ramírez-Alonso, G. M. D. J., Arzate-Quintana, C., & Camarillo‐Cisneros, J. (2023) · Molecular Diversity · doi:10.1007/s11030-023-10771-y · Cited by 26 · see citing works

Classification of Emg Signals Using Convolution Neural Network

Bakırcıoğlu, K., & Özkurt, N. (2020) · International Journal of Applied Mathematics Electronics and Computers · doi:10.18100/ijamec.795227 · Cited by 20 · see citing works

Behavioral Modeling of Power Amplifiers With Modern Machine Learning Techniques

Dikmese, S., Anttila, L., Campo, P. P., et al. (2019) · doi:10.1109/imc-5g47857.2019.9160381 · Cited by 20 · see citing works

Application of Convolutional Neural Networks for COVID-19 Detection in X-ray Images Using InceptionV3 and U-Net

Gupta, A., Mishra, S., Sahu, S. C., et al. (2023) · New Generation Computing · doi:10.1007/s00354-023-00217-2 · Cited by 19 · see citing works

Deep learning models for predictive maintenance: a survey, comparison, challenges and prospectPreprint

Serradilla, O., Zugasti, E., & Zurutuza, U. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.03207 · Cited by 16 · see citing works

A reinforcement learning based method for protein’s differential scanning calorimetry signal separation

Lv, X., Wang, S., Zhao, Y., et al. (2021) · Measurement · doi:10.1016/j.measurement.2021.110391 · Cited by 16 · see citing works

Comparative Study of Coupling Models of Feature Selection Methods and Machine Learning Techniques for Predicting Monthly Reservoir Inflow

Weekaew, J., Ditthakit, P., Pham, Q. B., et al. (2022) · Water · doi:10.3390/w14244029 · Cited by 11 · see citing works

Robotic Knitting

Treusch, P. (2020) · transcript Verlag eBooks · doi:10.1515/9783839452035 · Cited by 11 · see citing works

ACAU-Net: Atrous Convolution and Attention U-Net Model for Pavement Crack Segmentation

Jun, F., Li, J., Yichen, S., et al. (2022) · International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) · doi:10.1109/icceai55464.2022.00120 · Cited by 10 · see citing works

The Classification of Heartbeat PCG Signals via Transfer Learning

Almanifi, O. R. A., Razman, M. A. M., Musa, R. M., et al. (2021) · Lecture notes in electrical engineering · doi:10.1007/978-981-33-4597-3_5 · Cited by 9 · see citing works

COVID-19 Detection Using Chest X-Ray Images Based on Deep Learning

Sani, S., Bera, A., Mitra, D., et al. (2022) · International Journal of Software Science and Computational Intelligence · doi:10.4018/ijssci.312556 · Cited by 7 · see citing works

Using new artificial bee colony as probabilistic neural network for breast cancer data classification

Shah, H. (2021) · Frontiers in Engineering and Built Environment · doi:10.1108/febe-03-2021-0015 · Cited by 7 · see citing works

Análisis del desempeño de redes neuronales profundas para segmentación semántica en hardware limitado

División de Estudios de Posgrado e Investigación, T. N. D. M. I. T. C., Orozco, O. A. S., Sáenz, A. D. C., División de Estudios de Posgrado e Investigación, T. N. D. M. I. T. C., González, C. E. R., División de Estudios de Posgrado e Investigación, T. N. D. M. I. T. C., Quintana, J. A. R., & División de Estudios de Posgrado e Investigación, T. N. D. M. I. T. C. (2019) · RECIBE REVISTA ELECTRÓNICA DE COMPUTACIÓN INFORMÁTICA BIOMÉDICA Y ELECTRÓNICA · doi:10.32870/recibe.v8i2.142 · Cited by 7 · see citing works

CNN Based Joint Positioning and Pose Recognition of Concealed Human for 3D Through-Wall Imaging Radar

Xie, Z.-Y., Hu, J. P., Zhang, X., et al. (2021) · CIE International Conference on Radar (RADAR) · doi:10.1109/radar53847.2021.10028138 · Cited by 5 · see citing works

Research on Distribution Network Reconfiguration Based on Deep Q-learning Network

Di, H., Bao, Y., & Wang, B. (2020) · IEEE Conference on Energy Internet and Energy System Integration (EI2) · doi:10.1109/ei250167.2020.9346939 · Cited by 5 · see citing works

A Technology Acceptance Framework Inside the Indonesian Online Learning Platform

Harja, Y. D., Ambarwati, R., & Handiwibowo, G. A. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1783/1/012037 · Cited by 5 · see citing works

Smart Environment Monitoring Systems for PM2.5 Prediction Using Deep Learning Models in Smart City

Faydi, M., Zrelli, A., & Ezzedine, T. (2023) · International Symposium on Networks, Computers and Communications (ISNCC) · doi:10.1109/isncc58260.2023.10323707 · Cited by 4 · see citing works

A deep analysis of object capabilities for intelligence considering wireless IoT devices with the DNN approach

Senthil Kumaran, S., Balakannan, S. P., & Li, J. (2021) · The Journal of Supercomputing · doi:10.1007/s11227-021-04064-0 · Cited by 4 · see citing works

Deep Learning: A Heuristic Three-Stage Mechanism for Grid Searches to Optimize the Future Risk Prediction of Breast Cancer Metastasis Using EHR-Based Clinical Data

Jiang, X., Zhou, Y., Xu, C., Brufsky, A., & Wells, A. H. (2025) · Cancers · doi:10.3390/cancers17071092 · Cited by 3 · see citing works

Optimization Methods for Convolutional Neural Networks – The LeNet-5 Algorithm

Morsy, H. (2022) · International Journal of Recent Technology and Engineering (IJRTE) · doi:10.35940/ijrte.e7355.0111523 · Cited by 3 · see citing works

A literature review of the available artificial intelligence (AI) technology to assist in greening the Malaysian automotive industry

Husain, R., Wahab, N. A., & Gracious, M. S. D. (2022) · AIP conference proceedings · doi:10.1063/5.0120583 · Cited by 3 · see citing works

A neural network encoder-decoder for time series prediction: Application on 137Cs particulate concentrations in nuclearized rivers

Pelé, K., Nicoulaud-Gouin, V., & Lepage, H. (2024) · Ecological Informatics · doi:10.1016/j.ecoinf.2024.102463 · Cited by 3 · see citing works

Implementing Pattern Recognition and Matching techniques to automatically detect standardized functional tests from wearable technology

Vijayan, V., McKelvey, N., Condell, J., Gardiner, P., & Connolly, J. (2020) · 2020 31st Irish Signals and Systems Conference (ISSC) · doi:10.1109/issc49989.2020.9180174 · Cited by 3 · see citing works

Neural Networks for PAPR Reduction in Optical OFDM Signal Transmission

Zhang, W., Hajomer, A. A. E., Yang, X., & Hu, W. (2019) · International Conference on Transparent Optical Networks · doi:10.1109/icton.2019.8840567 · Cited by 3 · see citing works

Comparison of Optimization Techniques for Process Recognition Using Deep Neural Network

Képešiová, Z., Rosinová, D., & Kozák, Š. (2019) · doi:10.1109/accs-peit48329.2019.9062866 · Cited by 3 · see citing works

Fingerprint Presentation Attack Detection Using Transfer Learning Approach

Rani, R., & Singh, H. (2021) · International Journal of Intelligent Information Technologies · doi:10.4018/ijiit.2021010104 · Cited by 3 · see citing works

Forecasting of Carbon Monoxide Concentration Based on Sequence-to-Sequence Deep Learning Approach

Zaini, N., Ean, L. W., & Ahmed, A. N. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-90235-3_45 · Cited by 3 · see citing works

Encoding Techniques on Multivariate Time Series Signals for Failure Prevention of Industrial Assets with Unsupervised Deep Anomaly Detection

Bayram, F. S., Amin, M. N., Melke, A., et al. (2023) · IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) · doi:10.1109/icps58381.2023.10128068 · Cited by 3 · see citing works

Deep learning‐based gesture recognition for surgical applications: A data augmentation approach

Santiago, S. S., & Cifuentes, J. (2024) · Expert Systems · doi:10.1111/exsy.13706 · Cited by 2 · see citing works

A State-of-the-Art Review of Deep Learning-Based Object Detection Methods and Techniques

Gupta, C., Gill, N. S., & Gulia, P. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-4152-6_35 · Cited by 2 · see citing works

Maternal Risk Prediction During Pregnancy Through Machine Learning Using Mexican Women’s Data

Hernández-Chávez, R., Grijalva-González, Y. L., Guillen, B. O. E., et al. (2025) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-82123-3_9 · Cited by 2 · see citing works

Pattern matching techniques to automatically detect range of movement tests from wearable sensors

Vijayan, V., Connolly, J., Condell, J. V., Gardiner, P. V., & McKelvey, N. (2021) · Irish Signals and Systems Conference · doi:10.1109/issc52156.2021.9467875 · Cited by 2 · see citing works

Data-Driven Fault Localization of a DC Microgrid with Refined Data Input

Javed, W., & Chen, D. (2020) · IEEE International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie45063.2020.9152378 · Cited by 2 · see citing works

Development of a Smart Cooling System using Artificial Neural Network

Magsumbol, J.-A. V., Rosales, M. A., Valenzuela, I. C., et al. (2020) · IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) · doi:10.1109/hnicem51456.2020.9400111 · Cited by 2 · see citing works

Improving Clinical Prediction of Later Occurrence of Breast Cancer Metastasis Using Deep Learning and Machine Learning with Grid SearchPreprint

Jiang, X., & Xu, C. (2022) · Preprints.org · doi:10.20944/preprints202206.0394.v1 · Cited by 2 · see citing works

Applications of AI and Deep Learning in Biomedicine and Healthcare

Pujahari, R. M., Khan, R., & Yadav, S. P. (2024) · Advances in bioinformatics and biomedical engineering book series · doi:10.4018/979-8-3693-2426-4.ch006 · Cited by 1 · see citing works

ANN crowds in early-stage design: an investigation of influence of small training sets on prediction

Adebayo, O., Patel, A., & Summers, J. D. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.02.153 · Cited by 1 · see citing works

Prediction Method for Remaining Useful Life of Rolling Bearings Based on a Multi-layer Long Short-Term Memory Model

Tao, T., Yang, Y., Yang, T., et al. (2023) · International Conference on Electrical Engineering and Mechatronics Technology (ICEEMT) · doi:10.1109/iceemt59522.2023.10263212 · Cited by 1 · see citing works

Neural network classification of lithological units based on integrated radar and multispectral data

Rahmani, N., Ranjbar, H., Nezamabadipour, H., et al. (2024) · Acta Geodynamica et Geomaterialia · doi:10.13168/agg.2024.0022 · Cited by 1 · see citing works

Neural networks and behaviour based control for education botanical robot navigation

Burhanuddin, A., Supriyadi, S., & Malik, M. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1464/1/012002 · Cited by 1 · see citing works

Fingerprint Indoor Positioning Method with Deep Learning

Li, J., Hsu, W.-H., & Peng, C. (2019) · doi:10.1109/icice49024.2019.9117351 · Cited by 1 · see citing works

A Model Selection Algorithm for Complex Multi-Domain Cnn Systems Based on Feature-Weights Relation in Deep LearningPreprint

Alsaghir, E., Shi, X., & Silva, D. (2022) · Preprints.org · doi:10.20944/preprints202210.0081.v1 · Cited by 1 · see citing works

A Novel Multi Hidden Layer Convolutional Neural Network for Content Based Image Retrieval

Ramanjaneyulu, K., Veeraswamy, K., & Rao, C. S. (2020) · International Journal of Engineering and Advanced Technology · doi:10.35940/ijeat.c4771.029320

Modified Firearm Discharge Residue Analysis utilizing Advanced Analytical Techniques, Complexing Agents, and Quantum Chemical Calculations

Feeney, W. J. (2021) · doi:10.33915/etd.10302

Management of Unplanned Changes in Production Processes: AI Control Systems

Svigaris, Ž. (2022) · International Journal of Artificial Intelligence & Applications · doi:10.5121/ijaia.2022.13407

WSN-Based Secure and Energy-Efficient Smart Parking Management System (SPMS) Using FFA-ANN

Sharma, K. R., Sharma, T., Mittal, N., & Johar, A. K. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-99-7820-5_24

Leveraging Deep Learning, Grid Search, and Bayesian Networks to Predict Distant Recurrence of Breast Cancer

Jiang, X., Zhou, Y., Wells, A. H., & Brufsky, A. (2025) · Cancers · doi:10.3390/cancers17152515

Deep Learning for Predicting Late-Onset Breast Cancer Metastasis: The Single-Hyperparameter Grid Search (SHGS) Strategy for Meta-Tuning a Deep Feed-Forward Neural Network

Zhou, Y., Arora-Jain, O., & Jiang, X. (2025) · Bioengineering · doi:10.3390/bioengineering12111214

Deep Learning and Neural Networks in Cybersecurity

Avasthi, A., Jogi, N. L., Devi, S. N., Naidu, D. D. J. S., Balachander, T., Kadu, R. K., & Bhoopathy, V. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5223-7.ch002

Role and Application of Machine Learning Techniques in Early Diagnosis and Management of Autoimmune Diseases

Chadha, A., & Garg, N. (2026) · Springer eBooks · doi:10.1007/978-981-95-7490-2_16

Exploring neural networks and machine learning in predicting personal loan defaults

HOANG, H. T. T., Nguyen, N. M., & Ngo, D. (2026) · Risk Governance and Control Financial Markets & Institutions · doi:10.22495/rgcv16i2p11

An Assistive Object Recognition System for Visually Impaired Individuals Using Mask R-CNN

Khan, S. A., & Alzamel, M. (2026) · Journal of Disability Research · doi:10.57197/jdr-2026-0845

DETERMINING QUALITY REQUIREMENTS AT THE UNIVERSITIES TO IMPROVE THE QUALITY OF EDUCATION

Mustafa, N. H., Kelesbayev, D., & Alibekova, Z. D. (2018) · The Journal of Economic Research & Business Administration · doi:10.26577/be-2018-2-2141

Susquehanna Chorale Spring Concert "Roots and Wings"

Hawkins, D. (2017)

Using DataGrid Control to Realize DataBase of Querying in VB6.0

Hu, S. (2000) · Modern Computer

Study and Two Types of Typical Usage of DataGrid Web Server Control

Hai-tao, L. (2005) · Modern Computer

Achieving Parameter of DBSCAN Based on Datagrid

Xu, Q. (2010)