2014853.txt Apr 2026

: Research often cited in the context of industrial monitoring (like CNC machine tools) using spindle current data and deep learning.

: Grigori Sidorov, Francisco Velasquez, Efstathios Stamatatos, Alexander Gelbukh, and Liliana Chanona-Hernández

The identifier contains "2014" (the year) and "853" (a likely page number or reference ID). It strongly points to the following influential paper: 2014853.txt

: Expert Systems with Applications , Volume 41, Issue 3, pages 853–860 , 2014.

The ".txt" suffix often appears in two scenarios regarding academic papers: : Research often cited in the context of

: Some automated systems or repositories (like arXiv or ResearchGate ) export bibliographical data or full-text extractions as .txt files named after the publication year and ID. Other Potential "Deep" Papers

: Early influential work on using Deep Convolutional Neural Networks (CNNs) to break image-based security systems. 2014853.txt

: It may refer to a specific entry in a text-based dataset (like the PAN authorship attribution datasets) used to test the "deep" learning or machine learning models described in the paper.