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Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification.

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Joint Kinetics and Lumbar Curvatures during Symmetric Lifting: Squat and Stoop., , and . BMEI (2), page 818-822. IEEE Computer Society, (2008)978-0-7695-3118-2.NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars., , , and . CoRR, (2020)Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing., and . Neural Networks, (2021)Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing., , , , and . ACM Great Lakes Symposium on VLSI, page 619-624. ACM, (2023)Lower extremity joint moments during symmetric lifting: squat vs stoop., , , and . i-CREATe, page 101-104. ACM, (2007)TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training., , , , , and . DATE, page 1-6. IEEE, (2024)A Study for Web Site Color Guideline for Universal Access for Color Vision Deficiencies: Focusing on the Best General Hospitals in Korea and in the United States., , and . HCI (28), volume 373 of Communications in Computer and Information Science, page 246-250. Springer, (2013)Self-Training Of Graph Neural Networks Using Similarity Reference For Robust Training With Noisy Labels., , , and . ICIP, page 1951-1955. IEEE, (2020)Adaptive Graph Adversarial Networks for Partial Domain Adaptation., and . IEEE Trans. Circuits Syst. Video Technol., 32 (1): 172-182 (2022)RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems., , , and . CoRR, (2023)