http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Xuan-Thuy Vo (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
-
Minh Sang VO(Minh Sang VO ),Minh Quoc PHAM(Minh Quoc PHAM ),Thuy Bao Thu LE(Thuy Bao Thu LE ),Le Kim Ngan NGUYEN(Le Kim Ngan NGUYEN ),Xuan Tung DAO(Xuan Tung DAO ),Huynh To Nhi PHAM(Huynh To Nhi PHAM 한국유통과학회 2023 The Journal of Asian Finance, Economics and Busine Vol.10 No.2
The study aims to evaluate the impact of corporate social responsibility on customers’ repurchase intention in Vietnam’s fast-moving consumer goods (FMCG) industry. This study employs primary data surveyed from 417 Vietnamese consumers, and the sample is selected based on the willingness to participate in providing information. The results show corporate social responsibility’s positive impact on repurchase intention in the FMCG industry in the Vietnam market. There are three components of corporate social responsibility, including ethical responsibility, legal responsibility, and economic responsibility have a positive impact on repurchase intention. The economic responsibility component has the greatest effect on repurchase intention. There is not enough statistical basis for the philanthropic responsibility component of corporate social responsibility to recognize its impact on repurchase intention. The findings of this study suggest that companies dealing in the FMCG industry in Vietnam need to invest more in further developing their corporate social responsibility, it not only helps to improve their customer loyalty to businesses but also contributes to promoting the country’s economic and social development in a better and more sustainable direction.
-
3D SaccadeNet: A Single-Shot 3D Object Detector for LiDAR Point Clouds
Lihua Wen,Xuan-Thuy Vo,Kang-Hyun Jo 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
3D object detection is an essential step towards holistic scene understanding. Currently, the existing 3D object detection methods focus on certain object’s areas once and predict the object’s locations. The way does not conform to the habit of human observing targets. Hence, this work proposes a fast and accurate object detector called 3D SaccadeNet, which regards one 3D object as nine keypoints. In the training process, the corner loss, center loss, and classification loss are computed. However, the center is only used to predict a 3D object. Performed experiments on the KITTI dataset show that the proposed method is highly efficient and effective, and the 3D object detection reaches (91:18%; 82:80%; 79:90%).
-
TRAN, Quoc Thinh,VO, Thi Diu,LE, Xuan Thuy Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.3
In view of integration and development, compliance with regulations on information disclosure has important implications for users. Corporate social responsibility disclosure (CSRD) is an increasing concern of the community and society. CSRD always poses many challenges for the profitability of banks. The article uses the ordinary least square method to examine this relationship and employs timeseries data of five years from 18 Vietnamese listed banks from 2015 to 2019. The analysis is informed by Jensen and Meckling's Agency theory, Freeman's Stakeholder theory, and Dowling and Pfeffer's Legitimacy theory. The study results show that, with the CSRD dependent variable, return on assets (ROA) and net interest margin (NIM) have an opposite influence, but return on equity (ROE) has no effect on CSRD, while on the profitability dependent variable, CSRD has a different influence from ROA, ROE, and NIM. To enhance the relationship between CSRD and profitability, Vietnamese listed banks need to comply with CSRD as well as demonstrate responsibility to the community and society. Managers need to have clear development policies and strategies to ensure both profitability and responsibility regarding social and community activities. The State Securities Commission of Vietnam should enforce strict sanctions, conduct inspection, and complete evaluation criteria for Vietnamese listed banks.
-
Combination of Deep Learner Network and Transformer for 3D Human Pose Estimation
Tien-Dat Tran,Xuan-Thuy Vo,Duy-Linh Nguyen,Kang-Hyun Jo 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Deep neural networks (DNNs) have attained the maximum performance today not just for human pose estimation but also for other machine vision applications (e.g., semantic segmentation, object detection, image classification). Besides, the Transformer shows its good performance for extracting the information in temporal information for video challenges. As a result, the combination of deep learner and transformer gains a better performance than only the utility one, especially for 3D human pose estimation. At the start point, input the 2D key point into the deep learner layer and transformer and then use the additional function to combine the extracted information. Finally, the network collects more data in terms of using the fully connected layer to generate the 3D human pose which makes the result increased precision efficiency. Our research would also reveal the relationship between the use of the deep learner and transformer. When compared to the baseline-DNNs, the suggested architecture outperforms the aseline-DNNs average error under Protocol 1 and Protocol 2 in the Human3.6M dataset, which is now available as a popular dataset for 3D human pose estimation.
-
A Facial Gender Detector on CPU using Multi-dilated Convolution with Attention Modules
Adri Priadana,Muhamad Dwisnanto Putro,Xuan-Thuy Vo,Kang-Hyun Jo 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Facial gender detectors have evolved into a vital component of an intelligent advertisement display platform. It is helpful to assist a decision of delivering appropriate advertisements to each audience. To reduce system costs, applications deployed in this platform must be able to run on a CPU. This work proposes a facial gender detector (FGCPU) that can be implemented on a CPU device to support an advertising display platform. The proposed CNN model consists of a multi-dilated convolution with attention modules (MudaNet). The multi-dilated convolution is applied to capture multi-scale features in an efficient manner. The attention module is used to rectify the quality of the feature map. This work’s training and validation process is conducted on the UTKFace, the Labeled Faces in the Wild (LFW), and the Adience Benchmark datasets. As a result, the proposed CNN model is proven to compete with other common and lightweight competitors’ CNN models on these three datasets. Regarding speed, the detector can operate 49.19 frames per second in real-time on a CPU device.
ScienceON
스콜라연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
