Development of convolutional neural network and its application in image classification: a survey

Deep Residual Learning for Image Recognition

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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ImageNet classification with deep convolutional neural networks

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Adam: A Method for Stochastic Optimization

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Deep learning

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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

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ImageNet: A large-scale hierarchical image database

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Gradient-based learning applied to document recognition

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A Comparative Analysis of ResNet and MobileNet for Classifying MRI Images

Padmaja, D. L., Nikhil, B., Akshaya, B. S., & Deepak, G. S. (2024) · Lecture notes in electrical engineering · doi:10.1007/978-981-97-8031-0_3 · Cited by 1

Integrating CNN With PolInSAR Multidimensional Backscattering for Enhanced Forest Height Retrieval

Wang, L., Yang, L., Xiong, J., Shen, G., Fu, L., & Wang, H. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3595580 · Cited by 1

Detection of embryo eggs based on tensor depth calculation model

Zhang, M., & Wang, W. (2018) · International Conference on Image, Video Processing and Artificial Intelligence (IVPAI) · doi:10.1117/12.2513864 · Cited by 1

Image Target Recognition via Mixed Feature-Based Joint Sparse Representation

Wang, X., Tang, C., Li, J., Zhang, P., & Wang, W. (2020) · Computational Intelligence and Neuroscience · doi:10.1155/2020/8887453 · Cited by 1

Object Classification using Deep Neural Networks from Coded Diffraction Patterns

Morales, D., Jerez, A., & Argüello, H. (2021) · Symposium on Image, Signal Processing and Artificial Vision (STSIVA) · doi:10.1109/stsiva53688.2021.9591996 · Cited by 1

Medical Image Classification Based on Information Interaction Perception Mechanism

Wang, W., Hu, Y., Luo, Y., & Wang, X. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/8429899 · Cited by 1

Neurodevelopmental Age Estimation of Infants Using a 3D-Convolutional Neural Network Model based on Fusion MRI SequencesPreprint

Shabanian, M., Siddiqui, A., Chen, H., & DeVincenzo, J. P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.03963 · Cited by 3

Improved COVID-19 detection using data augmentation Deep Convolution GAN and classifier DenseNet.Preprint

Ghosh, D. (2021) · doi:10.21203/rs.3.rs-235624/v1 · Cited by 2

Quality Monitoring of Asphalt Concrete Pavement Construction with Real-Time Monitoring System Based on Digital TwinPreprint

Zhang, J., Tang, W., Zhu, Z., Skitmore, M., Philbin, S. P., Lu, Y., Liu, H., & Ni, Q. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4352104 · Cited by 1

Space Use-Case: Onboard Satellite Image Classification

Lemaire, E., Millet, P., Miramond, B., Bilavarn, S., Saoud, H., & Naik, A. S. (2020) · Springer eBooks · doi:10.1007/978-3-030-53532-2_12

Unify Language and Vision: An Efficient COVID-19 Tomography Image Classification ApproachPreprint

Shen, D. (2020) · doi:10.21203/rs.3.rs-104128/v1

Enhance Image Classification Performance Via Unsupervised Pre-trained Transformers Language ModelsPreprint

Shen, D. (2020) · doi:10.21203/rs.3.rs-93060/v1

A Multipulse Radar Signal Recognition Approach via HRF‐Net Deep Learning Models

Li, J., Zhang, H., Ou, J., & Wang, W. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/9955130

Radio Waveforms Classification via Deep Q Learning Network

Lai, S., Tao, M., Zhang, X., & Wang, L. (2021) · URSI General Assembly and Scientific Symposium · doi:10.23919/ursigass51995.2021.9560242

LTE Uplink Interference Inspection Using Convolutional Neural Networks

Medhat, A., Elattar, M., & Fahmy, O. M. (2021) · Novel Intelligent and Leading Emerging Sciences Conference (NILES) · doi:10.1109/niles53778.2021.9600524

Deep learning for vibration-based data-driven defect diagnosis of structural systems

Tang, H., Xie, Y., & Ran, L. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-817784-6.00018-7

Year in Review

Eismann, M. T. (2020) · Optical Engineering · doi:10.1117/1.oe.59.2.020101

A Deep Learning Approach for Detecting Diabetic Macular Edema through Analyzing Retinal Images

Mishra, A. S. D. N. (2022) · Mathematical Statistician and Engineering Applications · doi:10.17762/msea.v71i3s.21

In-Memory Computing Architectures for Big Data and Machine Learning Applications

Snåšel, V., Dang, T. K., Phạm, P. N. H., Küng, J., & Kong, L. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-8069-5_2

Application of Deep Convolutional Neural Network in Image Recognition

Aruzhan, M., & Alina, B. (2022) · IEEE International Conference on Smart Information Systems and Technologies (SIST) · doi:10.1109/sist54437.2022.9945797

Domain-Invariant Feature Alignment Using Variational Inference for Partial Domain Adaptation

Choudhuri, S., Adeniye, S., Sen, A., & Venkateswara, H. (2022) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/ieeeconf56349.2022.10052012

Convolutional Neural Network Approach for Iris Segmentation

Abhinand, P., Sheela, S. V., & Radhika, K. R. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-27609-5_28

Classification of Fashion E-Commerce Products Based on Resnet-Bert Multi-Modal Deep Learning and Transfer Learning Optimization MethodologyPreprint

Seo, I.-J., & Jang, B. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4485799

Automatic analysis of retinal images to aid in the diagnosis and grading of diabetic retinopathy

Romero-Oraá, R. (2022) · doi:10.35376/10324/59907

Detection of Oversized Objects in a Video Stream Using an Image Classification with Deep Neural Networks

Jamontt, P., Sarna, J., Wnuk, J., Bazan, M., Halawa, K., & Janiczek, T. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-37720-4_9

Contribución al mantenimiento de aisladores de alta tensión en servicio basado en medidas de corrientes de fuga

Barrachina, J. M. B. (2023) · doi:10.4995/thesis/10251/199256

Improving ResNet Model Accuracy with Curriculum Learning Using Blurred Images

Yin, Z., Zeng, Q., Pan, Q., & Zhuang, Y. (2023) · International Conference on High Performance Compilation, Computing and Communications (HP3C) · doi:10.1145/3606043.3606086

Heuristics to reduce linear combinations of activation functions to improve image classification

de Moraes, R. F., Evangelista, R. D. S., Pereira, A. L. D. S., Toledo, Y. P., Fernandes, L. A. F., & Martí, L. (2023) · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) · doi:10.1109/sibgrapi59091.2023.10347043

Detection of Driver Behaviours using Convolutional Neural Network with Modified Inception Module

Kadar, J. A., Dewi, M. A. K., Ramdan, A., Yuwana, R. S., Ihsan, C. N., Kusumo, B. S., Pratiwi, H., & Pardede, H. F. (2023) · International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET) · doi:10.1109/icramet60171.2023.10366592

Score-ranking smooth average precision loss for remote sensing image retrieval

Ge, Y., Liu, Q., Wu, G., Wang, S., & Ye, F. (2024) · Journal of Spatial Science · doi:10.1080/14498596.2024.2302167

Performance of convolutional neural networks on CIFAR and Dog Breed classification dataset

Bu, Y., Xiong, W., & Zhu, L. (2024) · Applied and Computational Engineering · doi:10.54254/2755-2721/40/20230650

Automatic Area Measurement of Ring Cooler Corner Images Based on EU-Net

Wang, W. A., Zhang, D., Li, Q., Li, J. K., Ma, J., & Xi, Y. (2023) · International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics (AIHCIR) · doi:10.1109/aihcir61661.2023.00012

ARTIFICIAL INTELLIGENCE AND ITS TOOLS IN PEST CONTROL FOR AGRICULTURAL PRODUCTION: A REVIEW

Mignoni, M. E., Monteiro, E. S., Zagonel, C., & Kunst, R. (2024) · RECIMA21 - Revista Científica Multidisciplinar · doi:10.47820/recima21.v5i5.5277

Deep Learning and Machine Learning Algorithms Methods in Cyber Security

Al-Absi, M. A., R’bigui, H., & Al-Absi, A. A. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-0573-3_22

A Unified Domain Transfer Framework for Image ClassificationPreprint

Karn, R. R. P., & Sanodiya, R. K. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4908096

Detection of Leukemia Using Transfer Learning

Das, B. K., Ghosh, C., Sheet, J., & Dutta, H. S. (2024) · doi:10.1002/9781394248438.ch24

Implementation Of Convolutional Neural Network (CNN) in The Android-Based Application for Detecting Coffee Bean Maturity

Muhlisin, E. I., Nurmalasari, R. R., Kamelia, L., & Sururie, R. W. (2024) · International Conference on Wireless and Telematics (ICWT) · doi:10.1109/icwt62080.2024.10674676

Künstliche Intelligenz im Stahlbau

Müller, A., Taras, A., & Kraus, M. A. (2025) · Wiley eBooks · doi:10.1002/9783433612125.ch9

Optimizing Deep Learning Networks for Image Classification Using the Rafflesia Optimization Algorithm

Chu, S., You, R., Pan, J., Kong, L., & Shieh, C. (2025) · Smart innovation, systems and technologies · doi:10.1007/978-981-97-8760-9_9

Development of an Intrinsically Safe Circuit Arc Simulation Platform and Characterization of Arc Discharge

Zhang, H., Jiang, H., Tang, G., Zhang, Z., Wang, A., Fang, W., Hao, Z., & Gao, C. (2025) · International Conference on Energy Systems and Electrical Power (ICESEP) · doi:10.1109/icesep66633.2025.11155546

Accurate Dating of Ancient Manuscripts with SIFT-CNN

Sakout, S., Nait-Hamoud, M. C., Gahmousse, A., Djeddi, C., & Ennaji, A. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-90893-4_12

Image Classification Based on Convolutional Neural Networks

Nandini, S., Deepthi, P., Bhavani, M., RubenRaju, K., Sindhuja, B., & Madhavi, A. (2025) · Lecture notes in electrical engineering · doi:10.1007/978-981-95-0269-1_180

Modeling social unrest: The geographical influence on social unrest prediction

Bedi, S., Samal, A. K., & Scott, S. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.131640

Learning multimodal interaction models in mixed societies

Malik, M. U. (2020) · theses.fr (ABES) · doi:10.70675/25fc786ez7f06z47dcz93b9z7439be248efb

Machine Learning Fault Diagnostic Techniques in Power Converters: A ReviewPreprint

Panah, S. F., Fakhrolmobasheri, A., Pashaei, M., Bozorgzad, P., Laaksonen, H. J. J., & Kauhaniemi, K. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6837686

Approximate Signed Multiplier Designs for Efficient CNN Inference

Zhang, M., Zhang, W., Hu, X., Geng, X., & Jiang, H. (2026) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas66217.2026.11562588

Custom tailored artificial neural network for laser pulse characterization

Gherman, A. M. M., Toşa, V., Kovács, K., Dumitru, A., Ursescu, D., & Tóth, I. (2026) · Optics & Laser Technology · doi:10.1016/j.optlastec.2026.115921

Prevención y gestión de accidentes en la minería subterránea peruana

Gomez, F. P. Z., & Aroquipa, H. (2025) · Universidad Nacional Autónoma de Tayacaja Daniel Hernández Morillo (UNAT) - Fondo Editorial. eBooks · doi:10.46908/ediunat.73

Computer vision–aided classification of insecticide-induced behavioral patterns in Aphis gossypii (Hemiptera: Aphididae)

Yoon, J., & Tak, J. (2026) · Journal of Economic Entomology · doi:10.1093/jee/toag246

Configurable-Accuracy Approximate Carry Disregard Multipliers for CNNs on FPGA

Lee, Y.-C., Liu, T.-W., & Lin, S.-Y. (2026) · IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan) · doi:10.1109/icce-taiwan71481.2026.11652640

Improved vision transformer for sports image classification via transfer learning and knowledge distillation

Li, C., Memmert, D., & Liu, Q. (2026) · PLoS ONE · doi:10.1371/journal.pone.0337744

The Evolution of Deep Learning Architectures for Visual Recognition: Design Principles, Feature Learning, and Network StrategiesPreprint

Xu, G., Zhang, J., Luo, J., Du, T., Li, C., Wu, X., Zhou, H., Xu, H., & Yu, Y. (2026) · Research Square · doi:10.21203/rs.3.rs-11102058/v1

An Optimized Architecture of Image Classification Using Convolutional Neural Network

Aamir, M., Rahman, Z.-U., Abro, W. A., Tahir, M., & Ahmed, S. M. (2019) · International Journal of Image Graphics and Signal Processing · doi:10.5815/ijigsp.2019.10.05 · Cited by 55

A Survey: Image Classification Models Based on Convolutional Neural Networks

Peng, L., Qiang, B., & Wu, J. (2022) · International Conference on Computer Research and Development · doi:10.1109/iccrd54409.2022.9730565 · Cited by 14

Evolution of Convolutional Neural Network Architecture in Image Classification Problems

Arsenov, A., Рубан, І. В., Smelyakov, K., & Chupryna, A. (2019) · International Scientific and Practical Conference "Information Technologies and Security" (ITS) · doi:10.55056/ceur-ws.org/vol-2318/paper4

Advances in Convolutional Neural Networks for Image Classification : Architecture Evolution, Transformer Fusion, and Application Expansion

Tang, J. (2025) · International Conference on Image Processing, Multimedia Technology and Machine Learning (IPMML) · doi:10.1109/ipmml68499.2025.11407192 · Cited by 1

Image Classification Using the Method of Convolutional Neural Networks

Huang, K. (2022) · IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) · doi:10.1109/tocs56154.2022.10016070 · Cited by 2