Image Classification Using Few Shot Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8438-1_7
Reference20 articles.
1. Sarkar NK, Singh MM, Nandi U (2022) Learning based image classification techniques. In: Mukhopadhyay S, Sarkar S, Dutta P, Mandal JK, Roy S (eds) Computational intelligence in communications and business analytics. CICBA 2022. Communications in computer and information science, vol 1579. Springer, Cham. https://doi.org/10.1007/978-3-031-10766-5-3
2. Krizhevsky A, Sutskever I, Hinton GE (2017) Imagenet classification with deep convolutional neural networks. Commun ACM 60(6):84–90
3. Sarkar NK, Singh MM, Nandi U (2022) Recent researches on image classification using deep learning approach. Int J Comput Digit Syst 12(1):1357–1374
4. Sarkar NK, Singh MM, Nandi U (2023) A novel deep neural network model using network deconvolution with attention based activation for crop disease classification. Multimed Tools Appl. https://doi.org/10.1007/s11042-023-16125-y
5. Liu B et al (2018) Deep few-shot learning for hyperspectral image classification. IEEE Trans Geosci Remote Sens 57(4):2290-2304
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