Dr. Lorenzo Lamberti
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  • Papers
    • TinyDEVO: Deep Event-Based Visual Odometry on Ultra-Low-Power Multi-Core Microcontrollers
    • Tiny-DroNeRF: Tiny Neural Radiance Fields Aboard Federated Learning-Enabled Nano-Drones
    • Distilling Tiny and Ultrafast Deep Neural Networks for Autonomous Navigation on Nano-UAVs
    • A Sim-to-Real Deep Learning-Based Framework for Autonomous Nano-Drone Racing
    • Combining Local and~Global Perception for~Autonomous Navigation on~Nano-UAVs
    • Bio-Inspired Autonomous Exploration Policies with CNN-based Object Detection on Nano-drones
    • Lightweight Neural Architecture Search for Temporal Convolutional Networks at the Edge
    • Tiny-PULP-Dronets: Squeezing Neural Networks for Faster and Lighter Inference on Multi-Tasking Autonomous Nano-Drones
    • Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering
    • Pruning In Time (PIT): A Lightweight Network Architecture Optimizer for Temporal Convolutional Networks
    • Automated Tuning of End-to-end Neural Flight Controllers for Autonomous Nano-drones
    • Low-Power License Plate Detection and Recognition on a RISC-V Multi-Core MCU-Based Vision System
    • Improving Autonomous Nano-Drones Performance via Automated End-to-End Optimization and Deployment of DNNs
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