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Reducing search space for fast pedestrian detection., and . VCIP, page 1-4. IEEE, (2015)Fast depth estimation using spatio-temporal prediction for stereo-based pedestrian detection., , and . VCIP, page 1-4. IEEE, (2015)Microscaling Data Formats for Deep Learning., , , , , , , , , and 23 other author(s). CoRR, (2023)Stereo-based region of interest generation for real-time pedestrian detection., and . Peer-to-Peer Netw. Appl., 8 (2): 181-188 (2015)Feature-based ROI generation for stereo-based pedestrian detection., , and . ICASSP, page 1727-1731. IEEE, (2017)Stereo based region of interest generation for pedestrian detection in driver assistance systems., , , and . ICIP, page 3386-3389. IEEE, (2013)With Shared Microexponents, A Little Shifting Goes a Long Way., , , , , , , , , and 12 other author(s). ISCA, page 83:1-83:13. ACM, (2023)Training Large Neural Networks with Constant Memory using a New Execution Algorithm., , , and . CoRR, (2020)Improving spatio-temporal feature extraction techniques and their applications in action classification., and . VCIP, page 1-6. IEEE, (2012)Shared Microexponents: A Little Shifting Goes a Long Way., , , , , , , , , and 12 other author(s). CoRR, (2023)