Research Article
Year 2023,
Volume: 5 Issue: 1, 57 - 66, 30.04.2023
Abstract
Tarım ürünleri arasında mısır bitkisi başlıca besin kaynakları içerisinde gösterilmektedir. Mısır bitkilerinde karşılaşılan önemli konulardan birisi ıslah sürecidir. Islah çalışmalarında tohumların haploid ve diploid tiplerinin belirlenmesi büyük önem taşımaktadır. Geleneksel olarak, gıda ürünlerinde haploid ve diploid mısır türlerinin saptanması için uzman analizi kullanılır. Uzman analizi, zaman alıcı, sübjektif ve pahalıdır. Bilgisayarlı görü tabanlı çözümler, tarımsal uygulamalar için oldukça makul gereksinimlerdir.
Bu çalışmada, haploit ve diploit mısırların aktif öğrenme kullanılarak saptanması için bir görüntüleme sistemi önerilmiştir. Geleneksel yaklaşımların aksine, sınıflandırıcı ile ilgili örneklerin algılanması ve etiketlenmesi için aktif bir öğrenme şeması kullanılır. Önerilen sistem kullanılarak, daha az sayıda örnekle daha yüksek doğruluğa sahip bir destek vektör sınıflandırıcı eğitilmiştir.
Supporting Institution
Yoktur
Project Number
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Thanks
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References
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Year 2023,
Volume: 5 Issue: 1, 57 - 66, 30.04.2023
Abstract
Project Number
-
References
- B.W. Boote, D.J. Freppon, G.N. de La Fuente, T. Lübberstedt, B.J. Nikolau, and E.A. Smith “Haploid differentiation in maize kernels based on fluorescence imaging”, Plant Breeding, vol. 35, no. 4, pp. 439-445 2016.
- G.N. de La Fuente, J.M. Carstensen, M.A. Edberg, and T. Lü bberstedt “Discrimination of haploid and diploid maize kernels via multispectral imaging”, Plant Breeding, vol. 136, no. 1, pp. 50-60, 2017.
- J. Lin, L. Yu, W. Li, and H. Qin “Method for Identifying Maize Haploid Seeds by Applying Diffuse Transmission Near-Infrared Spectroscopy”, Applied Spectroscopy, vol. 72, no. 4, pp. 611–617, 2018.
- Y. Altuntas, A.F. Kocamaz, R. Cengiz, and M. Esmeray “Classification of haploid and diploid maize seeds by using image processing techniques and support vector machines”, 26th IEEE Signal Processing and Communications Applications Conference, 2018.
- X.-Y. Wang, W.-X. Liao, D. An, and Y. Wei “Maize Haploid Identification via LSTM-CNN and Hyperspectral Imaging Technology”, CoRR arXiv, vol. abs/1805.0, 2018.
- L. Yu, W. Liu, W. Li, H. Qin, J. Xu, and M. Zuo “Non-destructive identification of maize haploid seeds using nonlinear analysis method based on their near-infrared spectra”, Biosystem Engineering, vol. 172, pp. 144-153, 2018.
- Y. Altuntaş, Z. Cömert, and A.F. Kocamaz “Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach”, Comp. and Elect. in Agr., vol. 163, pp. 1-11, 2019.
- E. Donmez “Discrimination of Haploid and Diploid Maize Seeds Based on Deep Features”, 28th Signal Processing and Communications Applications Conference, 2020.
- E. Dönmez “Classification of Haploid and Diploid Maize Seeds based on Pre-Trained Convolutional Neural Networks”, Celal Bayar Üniversitesi Fen Bilimleri Dergisi, vol. 16, no. 3, pp. 323–331, 2020.
- E. Dönmez “Enhancing classification capacity of CNN models with deep feature selection and fusion: A case study on maize seed classification”, Data and Know. Eng., vol. 141, p. 102075, pp. 1-12, 2022.
- A. Gunes, A.S. Bilgi, G. Ortac, H. Kalkan, and K. Tasdemir “Active learning method for classifying the mold contaminated figs”, 24th Signal Processing and Communication Application Conference, 2016.
- H. Kalkan, A. Güneş, E. Durmuş, and A. Kuşçu “Non-invasive detection of aflatoxin-contaminated figs using fluorescence and multispectral imaging”, Food Additives and Contaminants - Part A, vol. 31, no. 8, pp. 1414-1421, 2014.
- P. Pudil, J. Novovičová, and J. Kittler “Floating search methods in feature selection”, Pattern Recog. Lett., vol. 15, no. 11, pp. 1119-1125, 1994.
- D.D. Lewis and W.A. Gale “A sequential algorithm for training text classifiers”, 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1994.
- H.S. Seung, M. Opper, and H. Sompolinsky “Query by committee”, Fifth Annual ACM Workshop on Computational Learning Theory, 1992.
- C.E. Shannon “A Mathematical Theory of Communication”, Bell System Technical Journal, vol. 27, no. 3, pp. 379-423, 1948.
- T. Scheffer, C. Decomain, and S. Wrobel “Active hidden markov models for information extraction”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2189, 2001.
- K. Blinker “Incorporating Diversity in Active Learning with Support Vector Machines”, Twentieth International Conference on Machine Learning, 2003.
There are 18 citations in total.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Computer Software |
| Journal Section | Research Articles |
| Authors | |
| Project Number | - |
| Publication Date | April 30, 2023 |
| Published in Issue | Year 2023 Volume: 5 Issue: 1 |
