ABSTRACT: A new nano-based architectural design of multiple-stream convolutional homeomorphic error-control coding will be conducted, and a corresponding hierarchical implementation of important class ...
DeepSeek’s announced OCR (Optical Character Recognition) model compresses text-heavy data into images and reduces vision tokens per image by up to 20x while retaining 97% accuracy (10x compression) or ...
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Astronomy has a major data problem – simulating realistic images of the sky can help train algorithms
This article was originally published at The Conversation. The publication contributed the article to Space.com's Expert Voices: Op-Ed & Insights. Professional astronomers don’t make discoveries by ...
John Peterson does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond ...
A high-performance image compression algorithm is crucial for real-time information transmission across numerous fields. Despite rapid progress in image compression, computational inefficiency and ...
People store large quantities of data in their electronic devices and transfer some of this data to others, whether for professional or personal reasons. Data compression methods are thus of the ...
ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
Compression is a cornerstone of computational intelligence, deeply rooted in the theory of Kolmogorov complexity, which defines the minimal program needed to reproduce a given sequence. Unlike ...
Clustering methods are widely used in pattern recognition, data compression, data mining, but the problem of using them in real-time systems has not been a focus of most algorithm designers. In this ...
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