Ahmadi, I. (2025). Detection and classification of some diseases of tomato crops using transfer learning. Journal of Agricultural Machinery, 15(), 319–335. 3. https://doi.org/10.22067/jam.2024.88500.1258
Anjali, S., Pious, V., Sebastian, J. J., Krishnanunni, J., Johnson, J. K., Mujeeb, A., & Baselios, M. (2023). Multi-Stage Fruit Grading System. In Lecture Notes in Networks and Systems (Vol. 672). Springer.
Cullerne Bown, W. (2024). Sensitivity and specificity versus precision and recall, and related dilemmas. Journal of Classification, 41(2), 402–426. https://doi.org/10.1007/s00357-024-09478-y
Farahani, M., & Bagherpour, H. (2025). Using novel optimized deep learning techniques for detecting fungal infections in hazelnuts kernels based on shell color changes. Journal of Food Quality, 2025, Article ID 3350046. https://doi.org/10.1155/jfq/3350046
Golzar, S. H., Bagherpour, H., & Parian, J. A. (2024). A new method to optimize deep CNN model for classification of regular cucumber based on global average pooling. Journal of Food Processing and Preservation, 2024, Article ID 5818803. https://doi.org/10.1155/2024/5818803
Jahanbakhshi, A., Momeny, M., Mahmoudi, M., & Zhang, Y.-D. (2020). Classification of sour lemons based on apparent defects using stochastic pooling mechanism in deep convolutional neural networks. Scientia Horticulturae, 263, Article 109133. https://doi.org/10.1016/j.scienta.2019.109133
Kayaalp, K. (2024). A deep ensemble learning method for cherry classification. European Food Research and Technology, 250(7), 1513–1528. https://doi.org/10.1007/s00217-024-04490-3
Moallem, P., Serajoddin, A., & Pourghassem, H. (2017). Computer vision-based apple grading for Golden Delicious apples based on surface features. Information Processing in Agriculture, 4(1), 33–40. https://doi.org/10.1016/j.inpa.2016.10.003
Sabzi, S., Abbaspour-Gilandeh, Y., Javadikia, H., & Havaskhan, H. (2015). Automatic grading of emperor apples based on image processing and ANFIS [Görüntü işleme ve ANFIS ile emperor elmasının otomatik sınıflandırılması]. Tarım Bilimleri Dergisi, 21(3), 326–336. https://doi.org/10.1501/tarimbil_0000001335
Sultana, S., Tasir, M. A. M., Nobel, S. M. N., Kabir, M. M., & Mridha, M. F. (2024). XAI-FruitNet: An explainable deep model for accurate fruit classification. Journal of Agriculture and Food Research, 18(9), 101474. https://doi.org/10.1016/j.jafr.2024.101474
Tripathi, M. K., & Maktedar, D. D. (2022). Internal quality assessment of mango fruit: An automated grading system with ensemble classifier. The Imaging Science Journal, 70:4, 253-272, DOI: 10.1080/13682199.2023.2166657
Unay, D., Gosselin, B., Kleynen, O., Leemans, V., Destain, M.-F., & Debeir, O. (2011). Automatic grading of bi-colored apples by multispectral machine vision. Computers and Electronics in Agriculture, 75(1), 204–212. https://doi.org/10.1016/j.compag.2010.11.006
Vidyarthi, S. K., Singh, S. K., Tiwari, R., Xiao, H.-W., & Rai, R. (2020). Classification of first quality fancy cashew kernels using four deep convolutional neural network models. Journal of Food Process Engineering, 43(12), e13552. https://doi.org/10.1111/jfpe.13552
Vidyarthi, S. K., Singh, S. K., Xiao, H.-W., & Tiwari, R. (2021). Deep learnt grading of almond kernels. Journal of Food Engineering, 44(4). https://doi.org/10.1111/jfpe.13662 Process
