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Improving the reliability of 3D people tracking system by means of deep-learning., , and . IC3D, page 1-8. IEEE, (2016)Evaluation of variants of the SGM algorithm aimed at implementation on embedded or reconfigurable devices., and . IC3D, page 1-8. IEEE, (2016)Real-Time Self-Supervised Monocular Depth Estimation Without GPU., , , and . IEEE Trans. Intell. Transp. Syst., 23 (10): 17342-17353 (2022)Crosswalk Recognition Through Point-Cloud Processing and Deep-Learning Suited to a Wearable Mobility Aid for the Visually Impaired., , and . ICIAP Workshops, volume 9281 of Lecture Notes in Computer Science, page 282-289. Springer, (2015)On the confidence of stereo matching in a deep-learning era: a quantitative evaluation., , , , , , , and . CoRR, (2021)On the Synergies Between Machine Learning and Binocular Stereo for Depth Estimation From Images: A Survey., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 44 (9): 5314-5334 (2022)Near real-time Fast Bilateral Stereo on the GPU., , and . CVPR Workshops, page 136-143. IEEE Computer Society, (2011)Learning from scratch a confidence measure., and . BMVC, BMVA Press, (2016)Reliable Fusion of ToF and Stereo Depth Driven by Confidence Measures., , and . ECCV (7), volume 9911 of Lecture Notes in Computer Science, page 386-401. Springer, (2016)A wearable mobility aid for the visually impaired based on embedded 3D vision and deep learning., and . ISCC, page 208-213. IEEE Computer Society, (2016)