Zhang, H., Luo, T., Goh, R. S. M., & Wong, W.-F. (2023). Desire backpropagation: A lightweight training algorithm for multi-layer neural networks. Neurocomputing. (MNIST & Fashion-MNIST).

Raza, S. H., Islam, M. M., Haque, A., Farin, S., Ahmad, M., & Hossain, M. S. (2023). Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images. Engineering Applications of Artificial Intelligence, 126, 106902. https://doi.org/10.1016/j.engappai.2023.106902

Ge, S., Phan, K., Chen, S., Shen, T., Siriapisith, T., & Chen, M. (2023). Multi-class classification of brain tumor types from MR images using EfficientNets. Biomedical Signal Processing and Control, 84, 104777. https://doi.org/10.1016/j.bspc.2023.104777

Waskita, A., Nurhadiyatna, A., & co-authors. (2023). EfficientNetV2-based for MRI brain tumor image classification. In 2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA). https://doi.org/10.1109/IC3INA60834.2023.10285782

Chamnong, N., Werapun, J., & Hanskunatai, A. (2023). Hierarchical convolutional neural networks using CCP-3 block architecture for apparel image classification. International Journal of Advanced Computer Science and Applications, 14(6). https://doi.org/10.14569/IJACSA.2023.0140624

Riyanto, S., Sitanggang, I. S., Djatna, T., & Atikah, T. D. (2023). Comparative analysis using various performance metrics in imbalanced data for multi-class text classification. International Journal of Advanced Computer Science and Applications, 14(6). https://doi.org/10.14569/IJACSA.2023.01406116

Gerlinghoff, D., Luo, T., Goh, R. S. M., & Wong, W.-F. (2023). Desire backpropagation: A lightweight training algorithm for multi-layer spiking neural networks based on spike-timing-dependent plasticity. Neurocomputing, 560, 126773. https://doi.org/10.1016/j.neucom.2023.126773

Rani, R. U., Kakarla, J., & Sundar, B. (2023). Weather image classification using EfficientNet and dual attention block. In 2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN). https://doi.org/10.1109/ICSTSN57873.2023.10151564

Pillai, R., Sharma, N., & Gupta, R. (2023). Fine-Tuned EfficientNetB4 transfer learning model for weather classification. In 2023 3rd Asian Conference on Innovation in Technology (ASIANCON). https://doi.org/10.1109/ASIANCON58793.2023.10270698

Nagib, A. E., Mohamed, H., & Ashraf, A. (2023). Comparative analysis of pre-trained CNN architectures for multi-class weather classification: A study on deep learning techniques. In 2023 Intelligent Methods, Systems, and Applications (IMSA). https://doi.org/10.1109/IMSA58542.2023.10217616

Gupta, A., & Goel, S. (2023). Deep learning empowered weather image classification for accurate analysis. In 2023 IEEE 2nd International Conference on Industrial Electronics: Developments & Applications (ICIDeA). https://doi.org/10.1109/ICIDeA59866.2023.10295216

Samo, M., Mafeni Mase, J. M., & Figueredo, G. (2023). Deep learning with attention mechanisms for road weather detection. Sensors, 23(2), 798. https://doi.org/10.3390/s23020798

Afxentiou, V., & Vladimirova, T. (2023). Multi-label weather image classification for embedded computing platforms. In 2023 IEEE Smart World Congress (SWC). https://doi.org/10.1109/SWC57546.2023.10449086

Nguyen, T., & co-authors. (2023). MLcps: Machine Learning Cumulative Performance Score for classification problems. GigaScience, 12, giad108. https://doi.org/10.1093/gigascience/giad108

Obi, J., & co-authors. (2023). A comparative study of several classification metrics and their performances on data. World Journal of Advanced Engineering Technology and Sciences, 8(1), 308–314. https://doi.org/10.30574/wjaets.2023.8.1.0054

Swain, D., Sahoo, M., & Pradhan, S. (2023). An intelligent fashion object classification using CNN. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems. https://doi.org/10.4108/eetinis.v10i4.4315

Muhathir, N., Ryandra, M. F. D., Syah, R. B. Y., Khairina, N., & Muliono, R. (2023). Convolutional Neural Network (CNN) of Resnet-50 with Inceptionv3 Architecture in Classification on X-Ray Image. In Lecture notes in networks and systems (pp. 208–221). https://doi.org/10.1007/978-3-031-35314-7_20

Syah, R. B. Y., Muliono, R., Siregar, M. A., & Elveny, M. (2024). An efficiency metaheuristic model to predicting customers churn in the business market with machine learning-based. IAES International Journal of Artificial Intelligence, 13(2), 1547. https://doi.org/10.11591/ijai.v13.i2.pp1547-1556