최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기한국산업정보학회논문지 = Journal of the Korea Industrial Information Systems Research, v.28 no.5, 2023년, pp.1 - 14
전문석 (국립농업과학원 농업공학부) , 김영태 (국립농업과학원 농업생명자원부) , 정유석 (국립농업과학원 농업공학부) , 배효준 (국립농업과학원 농업공학부) , 이채원 (국립식량과학원 중부작물부) , 김송림 (국립농업과학원 농업생명자원부) , 최인찬 (국립농업과학원 농업공학부)
Soybeans are one of the world's top five staple crops and a major source of plant-based protein. Due to their susceptibility to climate change, which can significantly impact grain production, the National Agricultural Science Institute is conducting research on crop phenotypes through growth analys...
Aich, S. and Stavness, I. (2017). Leaf counting?with deep convolutional and deconvolutional?networks. In Proceedings of the IEEE?international conference on computer vision?workshops (pp. 2080-2089).
Bay, H., Tuytelaars, T. and Van Gool,?L.(2006). Surf: Speeded up robust features.?Lecture notes in computer science, 3951,?404-417. https://doi.org/10.1007/11744023_32.
Cho, J. H. (2006). Effect of planting date and?cultivation method on soybean growth in?paddy field. Korean journal of organic?agriculture, 14(2), 191-204.
Cho, C., Kim, D. Y., Choi, M. S., Jin, M. and?Seo, M. S. (2021). Efficient isolation and?gene transfer of protoplast in korean soybean?(Glycine Max (L.) Merr.) cultivars. Korean?journal of breeding science, 53(3), 230-239.
Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy,?A., Shuai, B., Liu, T., Wang, X., Wang, G.,?Cai, J. and Chen, T. (2018). Recent advances?in convolutional neural networks. Pattern?recognition, 77, 354-377.
Jeong, Y. S., Lee, H. R., Baek, J. H., Kim, K.?H., Chung, Y. S. and Lee, C. W. (2020).?Deep Learning-based rice seed segmentation?for phynotyping. Journal of the Korea?Industrial Information Systems Research.?25(5), 23-29.
Ko, K. E. and Sim, K. B. (2017). Trend of?object recognition and detection technology?using deep learning. Journal of Control?Robotics and Systems, 23(3), 17-24.
Krizhevsky, A., Sutskever, I. and Hinton, G.?E. (2017). Imagenet classification with deep?convolutional neural networks. Communications?of the ACM, 60(6), 84-90. https://doi.org/10.1145/3065386.
Karlekar, A. and Seal, A. (2020). SoyNet:?Soybean leaf diseases classification. Computers?and Electronics in Agriculture, 172, 105342.
LeCun, Y., Bottou, L., Bengio, Y., & Haffner,?P. (1998). Gradient-based learning applied to?document recognition. Proceedings of the?IEEE, 86(11), 2278-2324.
Lee, Y. H. and Kim, Y. (2020). Comparison of?CNN and YOLO for Object Detection.?Journal of the semiconductor & display?technology, 19(1), 85-92.
Lu, S., Song, Z., Chen, W., Qian, T., Zhang,?Y., Chen, M. and Li, G. (2021). Counting?dense leaves under natural environments?via an improved deep-learning-based object?detection algorithm. Agriculture, 11(10), 1003.
Pratama, M. T., Kim, S., Ozawa, S., Ohkawa,?T., Chona, Y., Tsuji, H. and Murakami, N.?(2020, July). Deep learning-based object?detection for crop monitoring in soybean?fields. In 2020 International Joint Conference?on Neural Networks (IJCNN) (pp. 1-7). IEEE.
Saleem, M. H., Potgieter, J. and Arif, K. M.?(2019). Plant disease detection and?classification by deep learning, Plants, 8(11), 468.
Teodoro, P. E., Teodoro, L. P. R., Baio, F. H.?R., da Silva Junior, C. A., dos Santos, R.?G., Ramos, A. P. M., Pinheiro, M. M. F.,?Osco, L. P., Goncalves, W. N., Carneiro, A.?M., Junior, J. M., Pistori, H. and?Shiratsuchi, L. S. (2021). Predicting days to?maturity, plant height, and grain yield in?soybean: A machine and deep learning?approach using multispectral data. Remote?Sensing, 13(22), 4632.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
Free Access. 출판사/학술단체 등이 허락한 무료 공개 사이트를 통해 자유로운 이용이 가능한 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.