May 26, 2023 · In this paper, we extend the current rate-distortion theory for machines, providing insight into important design considerations of machine- ...
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The proposed system initially uses deep learning-based UAV detection to locate the UAV and determine the ROI surrounding the detected UAVs. Afterward, the ROI ...
The volume of video consumed by machine is exceeding the volume of video consumed by humans. Machine vision tasks include object detection, segmentation, ...
Add Code · Rate-Distortion Theory in Coding for Machines and its Application · no code implementations • 26 May 2023 • Alon Harell, Yalda Foroutan, Nilesh Ahuja ...
This work proves, using the data processing inequality, that matching features from deeper layers is preferable in the sense of rate-distortion, ...
For the rest of this lecture, we introduce basic definitions for lossy compression schemes and introduce rate distortion theory. We present without proof ...
Rate-Distortion in Image Coding for Machines | Request PDF
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Most existing research on coding for machines focuses on the rate-accuracy trade-off, where rate measures the average number of bits per sample produced by ...
Jul 12, 2023 · Rate-distortion theory provides a powerful framework for understanding the nature of human memory by formalizing the relationship between information rate.
Rate-distortion theory is defined as the trade-off between source fidelity and coding rate, aiming to represent a source with the minimum number of bits ...
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Rate-distortion theory provides a powerful framework for understanding the nature of human memory by formalizing the relationship between information rate.