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MAVBench: Micro Aerial Vehicle Benchmarking., , , , , and . MICRO, page 894-907. IEEE Computer Society, (2018)Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots., , , , and . CoRR, (2019)Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?, , , , , , , , , and 1 other author(s). FPGA, page 5-14. ACM, (2017)A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+FPGA Platform: A Deep Learning Case Study., , , , , , , , , and . FPGA, page 107-116. ACM, (2018)The Role of Compute in Autonomous Aerial Vehicles., , , , , , , , , and . CoRR, (2019)2D feature tracking algorithm for motion analysis., and . Pattern Recognition, 28 (8): 1103-1126 (1995)MAVBench: Micro Aerial Vehicle Benchmarking., , , , , , , and . CoRR, (2019)Accelerating recurrent neural networks in analytics servers: Comparison of FPGA, CPU, GPU, and ASIC., , , , , and . FPL, page 1-4. IEEE, (2016)