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A Principled Hierarchical Deep Learning Approach to Joint ...
arXiv
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由 S Qi 著作2023 — Abstract page for arXiv paper 2310.19675: A Principled Hierarchical Deep Learning Approach to Joint Image Compression and Classification.
A Principled Hierarchical Deep Learning Approach to Joint Image ...
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一个重要的挑战是在连接通道的带宽有限的情况下，有效地训练这种分布式模型。我们的目标是优化具有低通道带宽的深度学习（DL）模型，同时仍然为高分类准确率提供特征信息。
Siyu Qi
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A Principled Hierarchical Deep Learning Approach to Joint Image Compression and Classification ... Our goal is to optimize DL models such that the encoder latent ...
Lahiru D. Chamain
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A Principled Hierarchical Deep Learning Approach to Joint Image Compression and Classification. S Qi, A Wijesinghe, LD Chamain, Z Ding. arXiv preprint arXiv ...
integrate image compression and classification via deep neural ...
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In this paper, a versatile framework is studied to explore the common feature representations for both image compression and classification. A fully shared ...
Image Compression
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In this paper, we propose a progressive learning paradigm for transformer-based variable-rate image compression. Paper
arXiv:2310.19675v1 [eess.IV] 30 Oct 2023
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由 S Qi 著作2023 — A PRINCIPLED HIERARCHICAL DEEP LEARNING APPROACH TO JOINT IMAGE. COMPRESSION AND CLASSIFICATION. Siyu Qi, Achintha Wijesinghe, Lahiru D ...
End-to-End Image Classification and Compression With ...
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This work develops an end-to-end networked learning framework by jointly optimizing the codec and classifier without reconstructing images for a given data ...
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UC Davis
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由 S Qi 著作2023 — With recent research progress, deep learning has become a major tool in multimedia appli- cations such as joint image compression and classification in the IoT ...
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A hierarchical deep learning framework for the consistent ...
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由 C Yang 著作2021被引用 19 次 — In this paper, a hierarchical deep learning framework is proposed to verify the land use information. For this purpose, a two-step strategy is applied.
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