Papers & publications.
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Optical Flow Methods for Interceptor Drones: A Critical Review
A critical review of 47 works (2021–2026) on optical-flow motion perception for autonomous counter-UAV interception — spanning classical, CNN (FlowNet, PWC-Net), RAFT, transformer (FlowFormer), edge, and event-camera methods, benchmarked by accuracy, speed, size, and power for SWaP-constrained drones.
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Edge AI and TinyML for Vision Applications in Autonomous Drones: A Systematic Critical Review
A systematic review of Edge AI and TinyML for on-board drone vision across five domains — comparing model compression (quantization, pruning, distillation) and accelerators (Jetson, Coral, Hailo-8, Loihi 2) under the weight, power, and thermal limits of UAV payloads.
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Bridging Strategic Reasoning and Tactical Execution with LLM and RL Agents
A survey synthesizing hierarchical architectures that pair LLM strategic planners with RL tactical controllers. Hybrid systems report ~28% higher task success and better sample efficiency than RL-only baselines on long-horizon autonomous-control tasks.
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Self-Managing Edge AI Systems for Intelligent Environments
A review of self-managing Edge AI for intelligent environments — smart homes, buildings, and tactical edge networks — covering model compression, runtime optimization, reinforcement learning, and federated learning for autonomous, resource-aware operation.
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Leveraging Lightweight AI for Anomaly Detection in Mechanical Power Transmission at the Edge
A TinyML model on an Arduino Nano 33 BLE Sense with an IMU detects DC-motor faults (loose, misaligned, noisy) from vibration signals — reaching 97.1% validation accuracy with millisecond on-device inference for low-cost predictive maintenance.
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AI-Powered CNN Model for Automated Lung Cancer Diagnosis in Medical Imaging
Int. J. of Statistics in Medical Research (2025)A convolutional neural network for automated lung-cancer classification on the IQ-OTHNCCD CT dataset (benign / malignant / normal), achieving 95% accuracy and a 0.95 F1-score. Peer-reviewed and published open access.