About the Journal
Indian Journal of Engineering Research Networking and Development aims to provide a comprehensive platform for researchers, academics, and professionals to publish, discover, and access high-quality scholarly journals across Computer Science disciplines. Our mission is to facilitate the dissemination of knowledge and foster collaboration within the academic community.
Key Features:
1. User-friendly Publication Platform: Indian Journal of Engineering Research Networking and Development offers a user-friendly interface for authors to submit their research papers, articles, and manuscripts. The submission process is streamlined, allowing authors to easily upload their work and track the status of their submissions.
2. Peer Review System: All submissions undergo a rigorous peer review process to ensure the quality and credibility of published content. Our platform enables efficient peer review management, with tools for reviewers to assess submissions and provide constructive feedback to authors.
3. Open Access Publishing: We support open access publishing, making research freely accessible to readers worldwide. Authors have the option to publish their work under open access licenses, promoting greater visibility and impact for their research.
4. Advanced Search and Discovery: Users can easily discover relevant research articles using our advanced search and filtering options. The website provides tools to explore journals, browse articles by category, keyword, or author, and stay updated with the latest publications in their areas of interest.
5. Community Engagement: Indian Journal of Engineering Research Networking and Development fosters a vibrant academic community by facilitating discussions, collaborations, and networking among researchers, scholars, and practitioners. Users can engage with content through comments, ratings, and sharing features.
6. Responsive Design: Our website is optimized for seamless browsing across desktop, tablet, and mobile devices, ensuring accessibility and usability for users on the go.
7. Editorial Board: Each journal on Indian Journal of Engineering Research Networking and Development is managed by an esteemed editorial board comprising experts in the respective field. The editorial board ensures the integrity and scholarly rigor of published content.
8. Analytics and Metrics: Authors and journal editors have access to comprehensive analytics and metrics to track the performance and impact of their publications. Metrics include citation counts, download statistics.
Future Developments:
1. Integration with ORCID: Implement integration with ORCID (Open Researcher and Contributor ID) to streamline author identification and authentication processes.
2. Enhanced Collaboration Tools: Develop features for collaborative research projects, such as shared document editing, project management, and communication tools for research teams.
3. AI-powered Recommendation System: Implement an AI-powered recommendation system to suggest relevant articles, journals, and researchers based on user preferences and browsing history.
4. Expanded Content Types: Introduce support for additional content types such as preprints, datasets, multimedia content, and supplementary materials to enhance the diversity of published research.
5. Global Outreach Initiatives: Launch initiatives to promote inclusivity and diversity in scholarly publishing, including translation services, mentorship programs, and partnerships with institutions in underrepresented regions.
Indian Journal of Engineering Research Networking and Development is committed to advancing the dissemination of knowledge and empowering researchers worldwide through our innovative platform.
Year of Starting:-2024
Format of Publication : Online
Subject:-The Indian Journal of Engineering Research Networking and Development is a premier peer-reviewed journal dedicated to advancing research and knowledge in the fields of computer Science .Our mission is to provide a platform for researchers, practitioners, and academics to publish high-quality, innovative, and impactful research that contributes to the development .
Current Issue
Vol. 1 No. 02 (2024): Missing Child Identification System using Deep Learning and Multiclass SVM
Abstract
The "Missing Child Identification System using Deep Learning and Multiclass SVM" is a groundbreaking project designed to address the pressing issue of locating and identifying missing children. Leveraging advanced technologies in the realms of deep learning and machine learning, this project aims to create a robust system for facial recognition and classification.
The deep learning component of the system utilizes state-of-the-art techniques to extract intricate facial features, generating comprehensive representations of each child. Simultaneously, a multiclass Support Vector Machine (SVM) is employed to classify and refine the identification process. The SVM acts as a classifier, distinguishing between different classes of facial features, thereby enhancing the accuracy of categorizing missing children.
The integration of deep learning and multiclass SVM in this project facilitates a more effective and efficient means of matching facial characteristics with existing databases. The result is a powerful tool that streamlines the identification process, enabling authorities to quickly and accurately reunite missing children with their families.
This project not only showcases the potential of cutting-edge technologies in addressing social issues but also underscores the significance of technology-driven solutions in humanitarian efforts. The "Missing Child Identification System" stands as a testament to the positive impact that technology can have on society, particularly in safeguarding the well-being and security of our most vulnerable population – our children.
Index terms
Missing Child Identification, Deep Learning, Multiclass SVM, Facial Recognition, Machine Learning, Social Impact, Humanitarian Technology, Child Safety, Database Matching, Technology Solutions, Vulnerable Populations, Reunification Efforts, Advanced Technologies, Facial Feature Extraction, Classifier Systems
Published:
2024-09-20
