1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jozefowicz, R., Jia, Y., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Schuster, M., Monga, R., Moore, S., Murray, D., Olah, C., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X., 2015.TensorFlow, Large-scale machine learning on heterogeneous systems.
2. Abhinav, K., SinghChauhan, J., Sarkar, D., 2018. Image segmentation of multi-shaped overlapping objects, in: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, INSTICC. SciTePress.pp.410–418.10.5220/0006628404100418.
3. Classification of three varieties of peach fruit using artificial neural network assisted with image processing techniques;Alipasandi;Int. J. Agron. Plant Prod.,2013
4. Image classification of root-trimmed garlic using multi-label and multi-class classification with deep convolutional neural network;Anh;Postharvest Biol. Technol.,2022
5. Identifying apple surface defects using principal components analysis and artificial neural networks;Bennedsen;Trans. ASABE,2007