19 papers · ranked by Valyu relevance
Daniel C. Stumpp, Himanshu Akolkar, Alan George, Ryad Benosman
—As the use of neuromorphic, event-based vision sensors expands, the need for compression of their output streams has increased. While their operational principle ensures event streams are spatially sparse, the high temporal resolution of the sensors can result in high data rates from the sensor depending on scene…
Xianzhi Zeng, Shuhao Zhang
—In the burgeoning realm of Internet of Things (IoT) applications on edge devices, data stream compression has become increasingly pertinent. The integration of added compression overhead and limited hardware resources on these devices calls for a nuanced software-hardware co-design. This paper introduces CStream, a…
Roman Dębski, Rafał Dreżewski, Francisco José García-Peñalvo
Sensor data streams often represent signals/trajectories which are twice differentiable (e.g., to give a continuous velocity and acceleration), and this property must be reflected in their segmentation. An adaptive streaming algorithm for this problem is presented. It is based on the greedy look-ahead strategy and is…
Yu M, Yufei Cui, Tei‐Wei Kuo, Chun Jason Xue
Deep-learning-based compressor has received interests recently due to much improved compression ratio. However, modern approaches suffer from long execution time. To ease this problem, this paper targets on cutting down the execution time of deep-learning-based compressors. Building historydependencies sequentially…
Dezhao Wang, Wenhan Yang, Yueyu Hu, Jiaying Liu
Learned image compression has achieved great success due to its excellent modeling capacity, but seldom further considers the Rate-Distortion Optimization (RDO) of each input image. To explore this potential in the learned codec, we make the first attempt to build a neural data-dependent transform and introduce a…
David Podgorelec, Damjan Strnad, Ivana Kolingerová, Borut Žalik + 1 more
'Jun Chen'] After a boom that coincided with the advent of the internet, digital cameras, digital video and audio storage and playback devices, the research on data compression has rested on its laurels for a quarter of a century. Domain-dependent lossy algorithms of the time, such as JPEG, AVC, MP3 and others…
Lebin Zhou, Cihan Ruan, Nam Ling, Wei Wang + 1 more
Tokenized visual representations have shown great promise in image compression, yet their extension to video remains underexplored due to the challenges posed by complex temporal dynamics and stringent bitrate constraints. In this paper, we propose Tokenized Video Compression (TVC), the first token-based dual-stream…
Qiyu Zha, Jiangling Guo, Hocine Cherifi
Video compression is central to large-scale video delivery, where better rate-distortion efficiency directly reduces bandwidth and storage cost. A practical way to improve efficiency is to encode a low-resolution video stream with a standard codec and restore high-resolution details with a learned super-resolution…
Michail Patsakis, Theodore Chronopoulos, Ioannis Mouratidis, Ilias Georgakopoulos-Soares
Genomic data repositories continue to grow as sequencing technologies improve, with the NCBI SRA alone exceeding 47 PB. General-purpose compressors treat bioinformatics files as unstructured byte streams and fail to exploit the structured nature of omics data. We present NYX, a format-aware compression system for…
Mohammad Hosseini
—Today, with the growing demands of information storage and data transfer, data compression is becoming increasingly important. Data Compression is a technique which is used to decrease the size of data. This is very useful when some huge files have to be transferred over networks or being stored on a data storage…
Martin Orf, Ronny Hannemann, Jonas Obleser
Amplitude compression is an indispensable feature of contemporary audio production and especially relevant in modern hearing aids. The cortical fate of amplitude-compressed speech signals is not well-studied, however, and may yield undesired side effects: We hypothesize that compressing the amplitude envelope of…
Timor Leiderman, Yosef Ben Ezra, Jun Chen
Video compression remains a challenging task despite significant advancements in end-to-end optimized deep networks for video coding. This study, inspired by information bottleneck (IB) theory, introduces a novel approach that combines IB theory with wavelet transform. We perform a comprehensive analysis of information…
Jeonghwan Heo, Jechang Jeong, Savio Sciancalepore, Giuseppe Piro + 1 more
'Nicola Zannone'] With the recent development of video compression methods, video transmission on traditional devices and video distribution using networks has increased in various devices such as drones, IP cameras, and small IoT devices. As a result, the demand for encryption techniques such as MPEG-DASH for…
Anders Andreasen, Maria Bonto, Fernando Montero
– This paper presents a framework for optimisation and techno-economic analysis of various pressurisation pathways for CO2 pipeline transportation. The pressurisation pathways include a conventional compression only case from initial to final pressure, a sub-critical compression part followed by cooling, liquefaction…
Rob Patro, Siddhant Bharti, Prajwal Singhania, Rakrish Dhakal + 2 more
The FASTQ file format is the lingua franca of primary data distribution and processing across most of bioinformatics. Over time, the compression, storage, transmission, and decompression of gzip compressed fastq.gz files has become a substantial scalability bottleneck in the modern world of fast and massively parallel…
Fajia Sun, Long Qian
DNA has been pursued as a compelling medium for digital data storage during the past decade. While large-scale data storage and random access have been achieved in artificial DNA, the synthesis cost keeps hindering DNA data storage from popularizing into daily life. In this study, we proposed a more efficient paradigm…
Luke Staniscia, Yun William Yu
Because of the rapid generation of data, the study of compression algorithms to reduce storage and transmission costs is important to bioinformaticians. Much of the focus has been on sequence data, including both genomes and protein amino acid sequences stored in FASTA files. Current standard practice is to use an…
Daniel Probst
Last year, a preprint gained notoriety, proposing that a k-nearest neighbour classifier is able to outperform large-language models using compressed text as input and normalised compression distance (NCD) as a metric. In chemistry and biochemistry, molecules are often represented as strings, such as SMILES for small…
Authors not listed
Cost effective and reliable hydrogen compression remains a challenging barrier in the wide-spread adoption of hydrogen as an energy carrier. The prevailing technology of mechanical compression suffers from several drawbacks, some of which can be addressed by non-mechanical compression strategies (e.g., electrochemical…