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Journal of Multimedia Technology & Recent Advancements

jomtra | E-ISSN: 2349-9028 | Peer-Reviewed | Hybrid Open Access

About the Journal

Journal of Multimedia Technology & Recent Advancements Journal of Multimedia Technology & Recent Advancements [2349-9028(e)] is a peer-reviewed hybrid open-access journal launched in 2014 that includes the hope to support future development of research and technologies in multimedia technology & … its advancements. Moreover, it welcomes diverse innovative ideas toward development and we will be to build sufficient grounds for the fulfillment of most different and promising ideas in this area.

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Journal of Multimedia Technology & Recent Advancements (JOMTRA): 2349-9028(e) is a peer-reviewed hybrid open-access journal launched in 2014. The basic principle for open source

Journal Information

Title:
Journal of Multimedia Technology & Recent Advancements
Abbreviation:
JOMTRA
Issues Per Year:
3 Issues (Jan-April,May-August,Sept-Dec)
P-ISSN:
2229-6999
Publisher:
116314
DOI:
10.37591/JOMTRA
Starting Year:
2010
Subject:
Language:
English
Publication Format:
Hybrid Open Access
Copyright Policy:
CC BY-NC-ND
Type:
Peer-reviewed Journal (Refereed Journal)
Address:

Editorial Board

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jomtra maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Dr. Rameshwar Shankarrao Kawitkar, Professor

Sinhgad College of Engineering, Maharashtra, India,

Email :

Latest Articles

Integration of AI and Blockchain: Benefits & Use Cases- A Review

The fusion of blockchain technology and artificial intelligence (AI) is a groundbreaking innovation that has the potential to revolutionize numerous sectors

Blockchain, AI, Distributed ledgers, Decentralization, Transparency

Attention-Enhanced YOLO Framework for Robust Real-Time Object Detection in Autonomous Driving Environments

Accurate object detection is essential for autonomous driving systems, where vehicles must continuously perceive surrounding road users and infrastructure in real time.

Autonomous vehicles, object detection, YOLO, attention mechanism, deep learning, real-time detection, computer vision, autonomous driving perception

Crowdsourced Real-Time Response with AR Assistance

The rapid growth of digital technologies has significantly transformed the way people interact with both virtual systems and the physical world.

Crowdsourcing, real-time matching, augmented reality, computer vision, machine learning, mobile computing, human-computer interaction, smart systems

AI-Driven Real-Time Traffic Monitoring and Intelligent Control System: A Unified Deep Learning Framework for Smart Urban Mobility Management

Urban traffic congestion imposes staggering economic and environmental costs on modern cities, with the INRIX Global Traffic Scorecard estimating annual per-driver productivity losses exceeding $1,348 in major metropolitan areas.

Intelligent traffic management, deep reinforcement learning, spatiotemporal graph networks, YOLOv8 vehicle detection, adaptive signal control, urban mobility, smart city, multi-agent systems, real-time traffic monitoring, incident detection

HabituraX: A Comprehensive Machine Learning System for Lifestyle-Based Disease Risk Prediction

The increased prevalence of lifestyle-related non-communicable diseases such as diabetes, obesity, and sleep disorders in the world requires the development of proactive risk-stratification tools.

Artificial intelligence, lifestyle diseases, National Health and Nutrition Examination Survey (NHANES), logistic regression, interpretability, feature engineering, multi-model architecture, preventive healthcare

Intelligent Big Data Processing: Optimizing Analytics Pipelines Through Ensemble Machine Learning, Distributed Computing, and Adaptive AI Architectures

Traditional data analytics methods are facing significant challenges due to the explosive rise of digital data.

Big data analytics, ensemble machine learning, Apache Spark, distributed computing, adaptive AI, stream processing, gradient boosting, Bayesian model averaging, IoT analytics, fault tolerance, energy-efficient AI

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