Classification of Natural Flower Videos Through Sequential Keyframe Selection Using SIFT and DCNN

Author:

Jyothi V. K.,Guru D. S.,Kumar Y. H. Sharath

Publisher

Springer Singapore

Reference27 articles.

1. Lin, H., Yang, X., Pei, J.: Key frame extraction based on multi scale phase based local features. In: ICSP2008 Proceedings. IEEE (2008). (978-1-4244-2179-4/08)

2. Guru, D.S., Sharath, Y.H., Manjunath, S.: Texture features and KNN in classification of flower images. In: IJCA Special Issue on “Recent Trends in Image Processing and Pattern Recognition", RTIPPR, pp. 21–29 (2010)

3. Guru, D.S., Sharath, Y.H., Manjunath, S.: Textural features in flower classification. Math. Comput. Model. 54, 1030–1036 (2011)

4. Das, M., Manmatha, R., Riseman, E.M.: Indexing flower patent images using domain knowledge. IEEE Intell. Syst. 14(5), 24–33 (1999)

5. Chatzigiorgaki, M., Skodras, A.N.: Real-time keyframe extraction towards video content identification. IEEE (2009). (978-1-4244-3298)

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1. Flower Classification in Videos: A HOG-PCA-NN Method;Algorithms for Intelligent Systems;2022

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