Zobrazeno 1 - 10
of 1 108
pro vyhledávání: '"Yang, Yuxiang"'
Autor:
Yang, Yuxiang, Shi, Guanya, Lin, Changyi, Meng, Xiangyun, Scalise, Rosario, Castro, Mateo Guaman, Yu, Wenhao, Zhang, Tingnan, Zhao, Ding, Tan, Jie, Boots, Byron
We focus on agile, continuous, and terrain-adaptive jumping of quadrupedal robots in discontinuous terrains such as stairs and stepping stones. Unlike single-step jumping, continuous jumping requires accurately executing highly dynamic motions over l
Externí odkaz:
http://arxiv.org/abs/2409.10923
Publikováno v:
Adv. Quantum Technol. 2400094 (2024)
This tutorial introduces a systematic approach for addressing the key question of quantum metrology: For a generic task of sensing an unknown parameter, what is the ultimate precision given a constrained set of admissible strategies. The approach out
Externí odkaz:
http://arxiv.org/abs/2409.07068
Quantum control plays a crucial role in enhancing precision scaling for quantum sensing. However, most existing protocols require perfect control, even though real-world devices inevitably have control imperfections. Here, we consider a fundamental s
Externí odkaz:
http://arxiv.org/abs/2409.04223
Goal-driven mobile robot navigation in map-less environments requires effective state representations for reliable decision-making. Inspired by the favorable properties of Bird's-Eye View (BEV) in point clouds for visual perception, this paper introd
Externí odkaz:
http://arxiv.org/abs/2409.01646
BTMuda: A Bi-level Multi-source unsupervised domain adaptation framework for breast cancer diagnosis
Deep learning has revolutionized the early detection of breast cancer, resulting in a significant decrease in mortality rates. However, difficulties in obtaining annotations and huge variations in distribution between training sets and real scenes ha
Externí odkaz:
http://arxiv.org/abs/2408.17054
Current 3D single object tracking methods primarily rely on the Siamese matching-based paradigm, which struggles with textureless and incomplete LiDAR point clouds. Conversely, the motion-centric paradigm avoids appearance matching, thus overcoming t
Externí odkaz:
http://arxiv.org/abs/2408.01688
Existing auto-regressive language models have demonstrated a remarkable capability to perform a new task with just a few examples in prompt, without requiring any additional training. In order to extend this capability to a multi-modal setting (i.e.
Externí odkaz:
http://arxiv.org/abs/2407.14875
Facial Expression Recognition (FER) holds significant importance in human-computer interactions. Existing cross-domain FER methods often transfer knowledge solely from a single labeled source domain to an unlabeled target domain, neglecting the compr
Externí odkaz:
http://arxiv.org/abs/2407.05688
Publikováno v:
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Localization is critical to numerous applications. The performance of classical localization protocols is limited by the specific form of distance information and suffer from considerable ranging errors. This paper foresees a new opportunity by utili
Externí odkaz:
http://arxiv.org/abs/2407.04703
Remarkable advances have been achieved in localization techniques in past decades, rendering it one of the most important technologies indispensable to our daily lives. In this paper, we investigate a novel localization approach for future computing
Externí odkaz:
http://arxiv.org/abs/2404.16895