Results of a prototype television bandwidth compression scheme

By A. H. Robinson, C. Cherry. 1967

How researchers see this paper

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Transfer without Forgetting (2022, neutral): “We finally point out that, as maps m take discrete binary values, one could profit from lossless compression algorithms (such as Run-Length Encoding [54] or LZ77 [71]) and thus store a compressed representation into the memory buffer.”
3LC: Lightweight and Effective Traffic Compression for Distributed Machine Learning (2018, methodology): “Zero-run encoding is a lossless transformation that shortens consecutive runs of common bytes (groups of ﬁve zero values) by using a variant of run-length encoding [31] specialized for quartic encoded data.”
Accelerating Convolutional Neural Networks via Activation Map Compression (2018, background): “[52] examine three approaches: run-length encoding [53], zero-value compression (ZVC) and zlib compression [1].”
Variable-rate discrete representation learning (2021, methodology): “One possible strategy is to use run-length encoding (Robinson & Cherry, 1967), which encodes runs of constant values in an input signal as (value , length) -tuples.”