SpectraSentinel: LightWeight Dual-Stream Real-Time Drone Detection, Tracking and Payload Identification
Shahriar Kabir, Istiak Ahmmed Rifti, H.M. Shadman Tabib, Mushfiqur Rahman, Sadatul Islam Sadi, Hasnaen Adil, Ahmed Mahir Sultan Rumi, Ch Md Rakin Haider

TL;DR
SpectraSentinel introduces a dual-stream, real-time drone detection system using separate IR and RGB YOLOv11n models, optimized for challenging environmental conditions and payload classification.
Contribution
It presents a novel dual-stream framework with specialized training for IR and RGB data, avoiding early fusion to improve drone detection and payload identification.
Findings
High accuracy in drone detection and payload classification
Real-time performance maintained across diverse conditions
Effective separation of IR and RGB processing enhances robustness
Abstract
The proliferation of drones in civilian airspace has raised urgent security concerns, necessitating robust real-time surveillance systems. In response to the 2025 VIP Cup challenge tasks - drone detection, tracking, and payload identification - we propose a dual-stream drone monitoring framework. Our approach deploys independent You Only Look Once v11-nano (YOLOv11n) object detectors on parallel infrared (thermal) and visible (RGB) data streams, deliberately avoiding early fusion. This separation allows each model to be specifically optimized for the distinct characteristics of its input modality, addressing the unique challenges posed by small aerial objects in diverse environmental conditions. We customize data preprocessing and augmentation strategies per domain - such as limiting color jitter for IR imagery - and fine-tune training hyperparameters to enhance detection performance…
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