Neural Vision Intelligence for Enterprise Applications Using Scalable Cloud Computing and Automated Image Recognition
DOI:
https://doi.org/10.15662/IJEETR.2023.0506031Keywords:
Neural Vision Intelligence, Enterprise Applications, Cloud Computing, Image Recognition, Deep Learning, Computer Vision, Artificial Intelligence, Automated Image Analysis, Scalable Computing, Visual IntelligenceAbstract
The rapid growth of visual data in enterprise environments has created a strong demand for intelligent systems capable of automatically processing, interpreting, and classifying images at scale. Conventional image-processing approaches often require extensive manual feature engineering and may struggle with the volume, diversity, and complexity of contemporary enterprise visual data. Neural vision intelligence, particularly through deep learning and automated image recognition, provides an opportunity to transform visual information into actionable enterprise intelligence. This study proposes a cloud-based framework that integrates neural vision models, scalable computing infrastructure, automated image recognition, distributed data processing, and enterprise application services. The framework is designed to support image classification, object detection, feature extraction, visual anomaly identification, and decision-support functions across enterprise workflows. Cloud computing provides elastic computational resources for model training and inference, while containerization and distributed processing support scalability and operational flexibility. The methodology follows a design-oriented research approach involving requirements analysis, dataset preparation, neural architecture development, cloud deployment, automated recognition pipeline design, and comprehensive performance evaluation. The proposed system is evaluated using accuracy, precision, recall, F1-score, inference latency, throughput, resource utilization, scalability, and robustness metrics. Attention is also given to data security, model monitoring, explainability, and integration with enterprise applications. The study aims to demonstrate how neural vision intelligence can provide scalable and automated visual analysis while reducing manual processing and supporting efficient, reliable, and intelligent enterprise operations
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