Zobrazeno 1 - 10
of 224
pro vyhledávání: '"Yu Zhaofei"'
Publikováno v:
中国工程科学, Vol 26, Iss 1, Pp 160-177 (2024)
Autonomous driving is an important research direction in computer vision which has broad application prospects. Pure vision perception schemes have significant research value in autonomous driving scenarios. Different from traditional cameras, spike
Externí odkaz:
https://doaj.org/article/22dc53a6b93e4acaadd44972eee07e06
Spiking Neural Networks (SNNs) are considered to have enormous potential in the future development of Artificial Intelligence (AI) due to their brain-inspired and energy-efficient properties. In the current supervised learning domain of SNNs, compare
Externí odkaz:
http://arxiv.org/abs/2410.07547
Autor:
Ma, Qichao, Zhu, Rui-Jie, Liu, Peiye, Yan, Renye, Zhang, Fahong, Liang, Ling, Li, Meng, Yu, Zhaofei, Wang, Zongwei, Cai, Yimao, Huang, Tiejun
Large Language Models (LLMs) have become pervasive due to their knowledge absorption and text-generation capabilities. Concurrently, the copyright issue for pretraining datasets has been a pressing concern, particularly when generation includes speci
Externí odkaz:
http://arxiv.org/abs/2410.04454
Autor:
Zhong, Xian, Hu, Shengwang, Liu, Wenxuan, Huang, Wenxin, Ding, Jianhao, Yu, Zhaofei, Huang, Tiejun
Spiking neural networks (SNNs) have garnered significant attention for their low power consumption and high biological interpretability. Their rich spatio-temporal information processing capability and event-driven nature make them ideally well-suite
Externí odkaz:
http://arxiv.org/abs/2409.12507
Spiking Neural Networks (SNNs) have emerged as a promising substitute for Artificial Neural Networks (ANNs) due to their advantages of fast inference and low power consumption. However, the lack of efficient training algorithms has hindered their wid
Externí odkaz:
http://arxiv.org/abs/2409.03368
Publikováno v:
中国工程科学, Vol 23, Iss 3, Pp 75-81 (2021)
Human beings might face significant security risks after entering into the artificial general intelligence (AGI) era. By summarizing the difference between AGI and traditional artificial intelligence, we analyze the sources of the security risks of A
Externí odkaz:
https://doaj.org/article/b98eff623d98424a998a4533f7e27613
Novel View Synthesis plays a crucial role by generating new 2D renderings from multi-view images of 3D scenes. However, capturing high-speed scenes with conventional cameras often leads to motion blur, hindering the effectiveness of 3D reconstruction
Externí odkaz:
http://arxiv.org/abs/2407.10062
Autor:
Wang, Lihao, Yu, Zhaofei
Spiking Neural Networks (SNNs) emulate the integrated-fire-leak mechanism found in biological neurons, offering a compelling combination of biological realism and energy efficiency. In recent years, they have gained considerable research interest. Ho
Externí odkaz:
http://arxiv.org/abs/2406.00405
Autor:
Zhang, Baoyue, Zheng, Yajing, Chen, Shiyan, Zhang, Jiyuan, Chen, Kang, Yu, Zhaofei, Huang, Tiejun
The amplification of high-speed micro-motions holds significant promise, with applications spanning fault detection in fast-paced industrial environments to refining precision in medical procedures. However, conventional motion magnification algorith
Externí odkaz:
http://arxiv.org/abs/2406.00383
Spiking neural networks (SNNs) are gaining popularity in deep learning due to their low energy budget on neuromorphic hardware. However, they still face challenges in lacking sufficient robustness to guard safety-critical applications such as autonom
Externí odkaz:
http://arxiv.org/abs/2405.20694