ImageNet Validation Set Compressed by the PDCTC Algortihm
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https://zenodo.org/doi/10.5281/zenodo.20483375
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This repository contains the results of the compression of ImageNet validation set (50,000 images, 1,000 classes) by Progressive DCT-based Coder (PDCTC) with the quality loss settings Q = 90
References
Progressive DCT-based Coder: Makarichev, V.; Lukin, V.; Brysina, I. Progressive DCT-Based Coder and Its Comparison to Atomic Function Based Image Lossy Compression. In Proceedings of the 2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, 22-26 February 2022; pp. 1-6. DOI: https://doi.org/10.1109/TCSET55632.2022.9766871.
ImageNet: Russakovsky, O.; Deng, J.; Su, H.; Krause, J.; Satheesh, S.; Ma, S.; Huang, Z.; Karpathy, A.; Khosla, A.; Bernstein, M.; Berg, A.C.; Fei-Fei, L. ImageNet Large Scale Visual Recognition Challenge. Int. J. Comput. Vis. 2015, 115, pp. 211--252. DOI: https://doi.org/10.1007/s11263-015-0816-y.
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Zenodo创建时间：
2026-06-01
