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Cloud Canvas: Orchestrating Distributed Image Processing

M. Bharathi, T. Aditya Sai Srinivas

Abstract


In this paper, we introduce a Distributed Image Processing Pipeline, leveraging deep learning and distributed computing for real-time image analysis. The pipeline aims to optimize resource utilization, implement advanced deep learning models, ensure data integrity, and minimize communication overhead. By distributing image processing tasks across a cluster of computing nodes, it enables faster processing and scalability. Integration of Apache Kafka and Apache Zookeeper enhances real-time stability and data distribution. The system's flexibility allows customization with diverse deep learning models and processing tasks. Applications span medical imaging, autonomous vehicles, satellite imagery, and industrial quality control, addressing complex image analysis challenges with accuracy and efficiency.


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References


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