Virtual Reality Video Image Based Fire Detection And Recognition System
Miss. Pardeshi Sanjana
, Miss. Sansare Mansi , Miss.Badwar Hrutika , Miss. Chavan Shraddha , Prof. Patil P.A.
SVM algorithm, Machine learning
Fire detection technology based on video images can avoid many flaws in conventional methods and detect fires. To achieve this, the support vector machine (SVM) method in machine learning theory has unique advantages, while rough set (RS) theory and SVM complement each other in application. Thus, a new classifier could be created by organically combining these methods to identify fires and provide fire warnings, yielding excellent noise suppression and promotion. Therefore, in this study, an RS is used as the front-end system for the SVM method, yielding improved performance than only SVM. Recognition time is reduced, and recognition efficiency is improved. Experiments show that the RS-SVM classifier model based on parameter optimization proposed in this paper mitigates deficiencies in overfitting and determining local extremum with excellent reliability and stability, and enhances the forecast accuracy of fires.
"Virtual Reality Video Image Based Fire Detection And Recognition System", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.202 - 206, May-2022, Available :https://ijsdr.org/papers/IJSDR2205039.pdf
Volume 7
Issue 5,
May-2022
Pages : 202 - 206
Paper Reg. ID: IJSDR_200336
Published Paper Id: IJSDR2205039
Downloads: 000347174
Research Area: Computer Engineering
Country: Andarsul, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
