Zobrazeno 1 - 10
of 449
pro vyhledávání: '"LIN, YIHAN"'
Autor:
Ouyang, Xiaomin, Wu, Jason, Kimura, Tomoyoshi, Lin, Yihan, Verma, Gunjan, Abdelzaher, Tarek, Srivastava, Mani
Multimodal sensing systems are increasingly prevalent in various real-world applications. Most existing multimodal learning approaches heavily rely on training with a large amount of complete multimodal data. However, such a setting is impractical in
Externí odkaz:
http://arxiv.org/abs/2411.12126
Autor:
Wang, Tongzhou, Lin, Yihan
CycleGAN provides a framework to train image-to-image translation with unpaired datasets using cycle consistency loss [4]. While results are great in many applications, the pixel level cycle consistency can potentially be problematic and causes unrea
Externí odkaz:
http://arxiv.org/abs/2408.15374
Autor:
Mlambo, Vongai C. *, Kirsch, Michael J., Masimbi, Ornella, Gasakure, Miguel, Alayande, Barnabas, Lin, Yihan
Publikováno v:
In Journal of Surgical Education October 2024 81(10):1331-1338
Autor:
Bryce-Alberti, Mayte, Wittenberg, Rachel E., Kirsch, Michael J., Bollinger, Daniel, Winslow, Kiana, Hey, Matthew T., Rauf, Raisa, Alayande, Barnabas, Anderson, Geoffrey A., Lin, Yihan
Publikováno v:
In The American Journal of Surgery January 2025 239
Spiking neural networks (SNNs) are known as a typical kind of brain-inspired models with their unique features of rich neuronal dynamics, diverse coding schemes and low power consumption properties. How to obtain a high-accuracy model has always been
Externí odkaz:
http://arxiv.org/abs/2203.01158
With event-driven algorithms, especially the spiking neural networks (SNNs), achieving continuous improvement in neuromorphic vision processing, a more challenging event-stream-dataset is urgently needed. However, it is well known that creating an ES
Externí odkaz:
http://arxiv.org/abs/2110.12211
Publikováno v:
In Cell Systems 18 September 2024 15(9):808-823
Autor:
Lin, Yihan, Li, Liheng, Tan, Longjie, Li, Yongliang, Ren, Xiangzhong, Zhang, Peixin, He, Chuanxin, Sun, Lingna
Publikováno v:
In Journal of Energy Chemistry August 2024 95:540-553
How to effectively and efficiently deal with spatio-temporal event streams, where the events are generally sparse and non-uniform and have the microsecond temporal resolution, is of great value and has various real-life applications. Spiking neural n
Externí odkaz:
http://arxiv.org/abs/2107.11711
Publikováno v:
In European Journal of Medicinal Chemistry 5 June 2024 272