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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | IMAGE SELECTION USING SELF SERVICE VISUAL ANALYTICS FOR UXO DETECTION |
| Authors Name: | Sivabalan S , Abinaya S , Gayathri A , Jayashree C , Rathika M |
| Download E-Certificate: | Download |
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IJNRD_218600
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| Published Paper Id: | IJNRD2404580 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Securing border zones poses a significant challenge for military forces, with the inability to monitor continuously resulting in tragic incidents and loss of life among soldiers. The surveillance and security of border zones remain critical concerns for military forces, with the challenging task of continuous monitoring often leading to tragic incidents and casualties among deployed personnel. To address this pressing issue, this project proposes an innovative approach leveraging the You Only Look Once (YOLO) deep learning model for bomb detection. In response to escalating concerns regarding public safety and terrorism threats, there is a growing demand for robust and efficient explosive detection systems. By harnessing the capabilities of YOLO, known for its speed and accuracy in object detection tasks, this system aims to enhance security measures along border zones. The proposed bomb detection system offers the potential to mitigate risks and protect military personnel by providing real-time detection and alert mechanisms, thereby bolstering national security efforts. Through the integration of advanced technology and machine learning algorithms, this solution strives to enhance situational awareness and safeguard lives in critical border regions. By deploying advanced machine learning algorithms, the system offers the potential to mitigate risks and prevent security breaches, thereby safeguarding both military personnel and civilian populations. Through the integration of cutting-edge technology and proactive security measures, this solution seeks to enhance situational awareness and strengthen national defence capabilities in border protection effort. |
| Keywords: | YOLO, Deep Learning, Image Processing, ROBOFLOW dataset, YAML File, Tensor Flow |
| Cite Article: | "IMAGE SELECTION USING SELF SERVICE VISUAL ANALYTICS FOR UXO DETECTION", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.f662-f666, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404580.pdf |
| Downloads: | 00029 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404580 Registration ID: 218600 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: f662-f666 Country: Perambalur, Tamil Nadu, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404580 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404580 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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