Zobrazeno 1 - 10
of 1 347
pro vyhledávání: '"Tao, Rui"'
Autor:
Georgakilas, Ioannis, Tiede, David, Urbonas, Darius, Bujalance, Clara, Caliò, Laura, Mirek, Rafał, Oddi, Virginia, Tao, Rui, Dirin, Dmitry N., Rainò, Gabriele, Boehme, Simon C., Galisteo-López, Juan F., Mahrt, Rainer F., Kovalenko, Maksym V., Miguez, Hernán, Stöferle, Thilo
The exploitation of the strong light-matter coupling regime and exciton-polariton condensates has emerged as a compelling approach to introduce strong interactions and nonlinearities into numerous photonic applications, ranging from low-threshold top
Externí odkaz:
http://arxiv.org/abs/2408.10667
Autor:
Feld, Leon G., Boehme, Simon C., Sabisch, Sebastian, Frenkel, Nadav, Yazdani, Nuri, Morad, Viktoriia, Zhu, Chenglian, Svyrydenko, Mariia, Tao, Rui, Bodnarchuk, Maryna, Lubin, Gur, Kazes, Miri, Wood, Vanessa, Oron, Dan, Rainò, Gabriele, Kovalenko, Maksym V.
In lead halide perovskites (APbX3), the effect of the A-site cation on optical and electronic properties has initially been thought to be marginal. Yet, evidence of beneficial effects on solar cell performance and light emission is accumulating. Here
Externí odkaz:
http://arxiv.org/abs/2404.15920
Autor:
Tao, Rui, Huang, Yuxing, Wang, Xiangdong, Yan, Long, Zhai, Lufeng, Ouchi, Kazushige, Li, Taihao
Weakly-supervised learning has emerged as a promising approach to leverage limited labeled data in various domains by bridging the gap between fully supervised methods and unsupervised techniques. Acquisition of strong annotations for detecting sound
Externí odkaz:
http://arxiv.org/abs/2309.11783
Learning meaningful frame-wise features on a partially labeled dataset is crucial to semi-supervised sound event detection. Prior works either maintain consistency on frame-level predictions or seek feature-level similarity among neighboring frames,
Externí odkaz:
http://arxiv.org/abs/2309.08355
Autor:
Qin, Tao-Rui, Chen, Zhuo-Hua, Liu, Tian-Xing, Chen, Fu-Yang, Duan, Hou-Jian, Deng, Ming-Xun, Wang, Rui-Qiang
We investigate the magnetotransport of topological Dirac semimetals (DSMs) by taking into account the Lifshitz transition of the Fermi arc surface states. We demonstrate that a bulk momentum-dependent gap term, which is usually neglected in study of
Externí odkaz:
http://arxiv.org/abs/2309.08233
Publikováno v:
Cell Death Discovery, Vol 10, Iss 1, Pp 1-13 (2024)
Abstract Mitophagy, a form of selective autophagy that removes damaged or dysfunctional mitochondria, plays a crucial role in maintaining mitochondrial and cellular homeostasis. Recent findings suggest that defective mitophagy is closely associated w
Externí odkaz:
https://doaj.org/article/a68398434ddd4b439dd0bbc3be696af2
Autor:
Guo, Zhifang, Mao, Jianguo, Tao, Rui, Yan, Long, Ouchi, Kazushige, Liu, Hong, Wang, Xiangdong
Text-based audio generation models have limitations as they cannot encompass all the information in audio, leading to restricted controllability when relying solely on text. To address this issue, we propose a novel model that enhances the controllab
Externí odkaz:
http://arxiv.org/abs/2308.11940
Multi-source adversarial transfer learning for ultrasound image segmentation with limited similarity
Autor:
Zhang, Yifu, Li, Hongru, Yang, Tao, Tao, Rui, Liu, Zhengyuan, Shi, Shimeng, Zhang, Jiansong, Ma, Ning, Feng, Wujin, Zhang, Zhanhu, Zhang, Xinyu
Lesion segmentation of ultrasound medical images based on deep learning techniques is a widely used method for diagnosing diseases. Although there is a large amount of ultrasound image data in medical centers and other places, labeled ultrasound data
Externí odkaz:
http://arxiv.org/abs/2305.19069
Publikováno v:
Fayixue Zazhi, Vol 40, Iss 3, Pp 254-260 (2024)
ObjectiveTo establish a rapid， accurate， and sensitive multiplex PCR detection method for the simultaneous identification of the six common edible meats （beef， lamp， chicken， pork， goose， duck）， and to evaluate its application val
Externí odkaz:
https://doaj.org/article/6456580e8f52483a8faf9f1f9eb1037f
Autor:
Li, Yiming, Guo, Zhifang, Ye, Zhirong, Wang, Xiangdong, Liu, Hong, Qian, Yueliang, Tao, Rui, Yan, Long, Ouchi, Kazushige
In this paper, we describe in detail our system for DCASE 2022 Task4. The system combines two considerably different models: an end-to-end Sound Event Detection Transformer (SEDT) and a frame-wise model, Metric Learning and Focal Loss CNN (MLFL-CNN).
Externí odkaz:
http://arxiv.org/abs/2210.09529