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Starter code for RiverCrossing project.

The D.C. Crime Insights Application is a comprehensive platform designed to provide daily updated and historical crime data, helping users make informed safety decisions. It integrates advanced analytics, machine learning, and natural language processing (NLP) to offer intuitive and personalized crime reporting and safety features.

With growing concerns about public safety, existing crime data tools often lack accessibility, timely updates, and user-friendly interfaces. Our application bridges the gap by leveraging open-source data from federal and local agencies, advanced analytics, and user-centric design to deliver actionable safety insights.

We aim to automatically classify images into specific scene types, such as “beach”, “forest”, “city street”, or “office”. This can provide a nuanced understanding of different environments, improve content- based image retrieval, enhance autonomous navigation, and support detailed analytics in industries such as tourism, marketing, and real estate. The target audience would be developers and companies in media organizations, content-based search, autonomous vehicle navigation, and location-based services.

Most of the Implementation is under the CNN Implementation Branch

Python API client for accessing LINbase and genomeRxiv functionality through commandline

This project involves developing an AI-powered Open-Source Intelligence (OSINT) platform to detect and combat misinformation on social media. It uses machine learning, NLP, and computer vision techniques to analyze textual and visual content, providing real-time alerts and insights to enhance public trust.