Zobrazeno 1 - 10
of 247
pro vyhledávání: '"Takiguchi, Tetsuya"'
This paper introduces a zero-shot sound event classification (ZS-SEC) method to identify sound events that have never occurred in training data. In our previous work, we proposed a ZS-SEC method using sound attribute vectors (SAVs), where a deep neur
Externí odkaz:
http://arxiv.org/abs/2303.10316
The ability to record high-fidelity videos at high acquisition rates is central to the study of fast moving phenomena. The difficulty of imaging fast moving scenes lies in a trade-off between motion blur and underexposure noise: On the one hand, reco
Externí odkaz:
http://arxiv.org/abs/2211.16034
Recent works have shown the ability of Implicit Neural Representations (INR) to carry meaningful representations of signal derivatives. In this work, we leverage this property to perform Video Frame Interpolation (VFI) by explicitly constraining the
Externí odkaz:
http://arxiv.org/abs/2206.10886
This paper proposes a novel neuronal current source localization method based on Deep Prior that represents a more complicated prior distribution of current source using convolutional networks. Deep Prior has been suggested as a means of an unsupervi
Externí odkaz:
http://arxiv.org/abs/2203.13981
Autor:
Tsunoda, Koichi, Ishii, Toyota, Kuroda, Hiroyuki, Nakatani, Hiroaki, Tateda, Masaru, Masuda, Sawako, Takiguchi, Tetsuya, Tanaka, Fujinobu, Misawa, Hayato, Senarita, Masamitsu, Takazawa, Mihiro, Itoh, Kenji, Baer, Thomas
Publikováno v:
In Heliyon 29 February 2024 10(4)
Autor:
Tristan, Hascoet, Zhang, Yihao, Andreas, Persch, Takashima, Ryoichi, Takiguchi, Tetsuya, Ariki, Yasuo
Maintaining aging infrastructure is a challenge currently faced by local and national administrators all around the world. An important prerequisite for efficient infrastructure maintenance is to continuously monitor (i.e., quantify the level of safe
Externí odkaz:
http://arxiv.org/abs/2010.11780
Training Convolutional Neural Networks (CNN) is a resource intensive task that requires specialized hardware for efficient computation. One of the most limiting bottleneck of CNN training is the memory cost associated with storing the activation valu
Externí odkaz:
http://arxiv.org/abs/1910.11127
Many recent advances in computer vision are the result of a healthy competition among researchers on high quality, task-specific, benchmarks. After a decade of active research, zero-shot learning (ZSL) models accuracy on the Imagenet benchmark remain
Externí odkaz:
http://arxiv.org/abs/1904.04957
Autor:
Guo, Xingchen, Xu, Xuexin, Chen, Xunquan, Chen, Jinhui, Jia, Rong, Zhang, Zhihong, Takiguchi, Tetsuya, Hancock, Edwin R.
Publikováno v:
In Pattern Recognition September 2022 129
Publikováno v:
Energy & Environment, 2020 Dec 01. 31(8), 1416-1447.
Externí odkaz:
https://www.jstor.org/stable/26960871