Real-Time Visual Intelligence on Low-Cost UAVs: A Modular Approach for Tracking, Scanning, and Navigation
Autonomous drones are rapidly transforming modern warfare and civil applications alike. This paper presents the development of an integrated intelligent drone system designed to serve as a personal assistant. Leveraging the DJI Tello drone platform, we implemented a modular architecture that integrates three core artificial intelligence functionalities: facial detection, facial recognition, and depth estimation from monocular vision. A web-based interface enables seamless drone control and real-time video monitoring, while a Python-based server processes visual data and executes inference pipe
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 50%Into the Omniverse: Three Workflows for Improving Vision AI Agent Accuracy With Synthetic Data and Fine-Tuning →
- PossiblePossibly related (embedding) · 47%open-edge-platform/geti →
- PossiblePossibly related (embedding) · 46%DoubangoTelecom/compv →
- PossiblePossibly related (embedding) · 46%heypinchy/pinchy →
- LinkedLinked via arxiv author · 85%Andrei-Marian Ungureanu →
“Real-Time Visual Intelligence on Low-Cost UAVs: A Modular Approach for Tracking, Scanning, and Navigation”
- LinkedLinked via arxiv author · 85%Stelian Spînu →
“Real-Time Visual Intelligence on Low-Cost UAVs: A Modular Approach for Tracking, Scanning, and Navigation”
- PossiblePossibly related (embedding) · 49%dronelabourlm/dllm-python →
- PossiblePossibly related (embedding) · 59%Agentic vision: Building visual intelligence with Amazon Bedrock and MCP servers →