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Improving the reliability of 3D people tracking system by means of deep-learning.

, , и . IC3D, стр. 1-8. IEEE, (2016)

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Stefano Cracolici

Stefano Meini

Stefano Cardanobile

Stefano Carignano

Giovanni Stefano

 

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Crosswalk Recognition Through Point-Cloud Processing and Deep-Learning Suited to a Wearable Mobility Aid for the Visually Impaired., , и . ICIAP Workshops, том 9281 из Lecture Notes in Computer Science, стр. 282-289. Springer, (2015)Improving the reliability of 3D people tracking system by means of deep-learning., , и . IC3D, стр. 1-8. IEEE, (2016)Evaluation of variants of the SGM algorithm aimed at implementation on embedded or reconfigurable devices., и . IC3D, стр. 1-8. IEEE, (2016)Cross-Spectral Neural Radiance Fields., , , , , и . 3DV, стр. 606-616. IEEE, (2022)Reliable Fusion of ToF and Stereo Depth Driven by Confidence Measures., , и . ECCV (7), том 9911 из Lecture Notes in Computer Science, стр. 386-401. Springer, (2016)Near real-time Fast Bilateral Stereo on the GPU., , и . CVPR Workshops, стр. 136-143. IEEE Computer Society, (2011)A wearable mobility aid for the visually impaired based on embedded 3D vision and deep learning., и . ISCC, стр. 208-213. IEEE Computer Society, (2016)A sufficient condition based on the Cauchy-Schwarz inequality for efficient template matching., и . ICIP (1), стр. 269-272. IEEE, (2003)Fast Stereo Matching for the VIDET System using a General Purpose Processor with Multimedia Extensions., и . CAMP, стр. 356-. IEEE Computer Society, (2000)Template Matching Based on the L_p Norm Using Sufficient Conditions with Incremental Approximations., , и . AVSS, стр. 20. IEEE Computer Society, (2006)