Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Yu-Ding Lu"'
Autor:
Shih-Hau Fang, Hao-Hsiang Liao, Yu-Xiang Fei, Kai-Hsiang Chen, Jen-Wei Huang, Yu-Ding Lu, Yu Tsao
Publikováno v:
Sensors, Vol 16, Iss 8, p 1324 (2016)
This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improve
Externí odkaz:
https://doaj.org/article/55f41176cd834ee9b64c43d601bb96fa
Autor:
Yu-Ding Lu, 盧育鼎
97
This research used the users of YouTube as a sample to realize what reasons the users in Taiwan wanted to use YouTube and the actual usage of circumstances. According to forward, the research cited Unified Theory of Acceptance and Use of Tech
This research used the users of YouTube as a sample to realize what reasons the users in Taiwan wanted to use YouTube and the actual usage of circumstances. According to forward, the research cited Unified Theory of Acceptance and Use of Tech
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/94243331742848834724
Face anti-spoofing (FAS) plays a critical role in securing face recognition systems from different presentation attacks. Previous works leverage auxiliary pixel-level supervision and domain generalization approaches to address unseen spoof types. How
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1ca0b73786e5596b95da680acc6de8e
http://arxiv.org/abs/2203.14325
http://arxiv.org/abs/2203.14325
Publikováno v:
ICIP
Spatial audio is an essential medium to audiences for 3D visual and auditory experience. However, the recording devices and techniques are expensive or inaccessible to the general public. In this work, we propose a self-supervised audio spatializatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::558cba2ab2a6f290d0ebf16525c96558
https://doi.org/10.1109/icip.2019.8803494
https://doi.org/10.1109/icip.2019.8803494
Autor:
Hsin-Ying Lee, Hung-Yu Tseng, Qi Mao, Jia-Bin Huang, Yu-Ding Lu, Maneesh Singh, Ming-Hsuan Yang
Image-to-image translation aims to learn the mapping between two visual domains. There are two main challenges for this task: 1) lack of aligned training pairs and 2) multiple possible outputs from a single input image. In this work, we present an ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3bdb4bb0567bdff66710e01f5ac7a1b8
http://arxiv.org/abs/1905.01270
http://arxiv.org/abs/1905.01270
Publikováno v:
ICASSP
In this study, we investigate on the effects of deep learning based speech enhancement as a preprocessor to speaker diarization in quite challenging realistic environments involving the background noises, reverberations and overlapping speech. To imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8a485cc27d2851e3a80408b09cd179b
https://doi.org/10.1109/icassp.2018.8462311
https://doi.org/10.1109/icassp.2018.8462311
Publikováno v:
ICASSP
This paper presents a learning and scoring framework based on neural networks for speaker verification. The framework employs an autoencoder as its primary structure while three factors are jointly considered in the objective function for speaker dis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be6a9601f6001ea1848250ce6a27d966
https://doi.org/10.1109/icassp.2017.7953183
https://doi.org/10.1109/icassp.2017.7953183
Autor:
Yu-Ding Lu, Yu Tsao, Jen-Wei Huang, Shih-Hau Fang, Yu Xiang Fei, Kai Hsiang Chen, Hao Hsiang Liao
Publikováno v:
Sensors, Vol 16, Iss 8, p 1324 (2016)
Sensors; Volume 16; Issue 8; Pages: 1324
Sensors (Basel, Switzerland)
Sensors; Volume 16; Issue 8; Pages: 1324
Sensors (Basel, Switzerland)
This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::272f89a5b01fe2c75814cbc103790762
http://www.mdpi.com/1424-8220/16/8/1324
http://www.mdpi.com/1424-8220/16/8/1324