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Deep learning (DL) has proven to be an effective machine learning and computer vision technique.
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O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein et al. , “Imagenet large scale visual recognition challenge,” International journal of computer vision , vol. 115, no. 3, pp. 211–252, 2015
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2016
Cited alongside, same era.
M. Sundararajan, A. Taly, and Q. Yan, “Axiomatic attribution for deep networks,” in International Conference on Machine Learning . PMLR, 2017, pp. 3319–3328
2017
Cited alongside, same era.
2018
Cited alongside, same era.
K. Yun, “Accelerating autonomy in space using memory-centric architectures for deep neural networks,” IEEE Space Computing Conference , 2019
2019
Cited alongside, same era.
F. Emmert-Streib, Z. Yang, H. Feng, S. Tripathi, and M. Dehmer, “An introductory review of deep learning for prediction models with big data,” Frontiers in Artificial Intelligence , vol. 3, p. 4, 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
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