Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Vu Minh Hieu"'
Autor:
Muhammad Sadiq, Massoud Moslehpour, Ranfeng Qiu, Vu Minh Hieu, Khoa Dang Duong, Thanh Quang Ngo
Publikováno v:
Journal of Innovation & Knowledge, Vol 8, Iss 1, Pp 100290- (2023)
Sustainable development goals (SDGs) are the foremost requirement of the entire world, and a sharing economy is potentially the best way to achieve them, a phenomenon which needs to be emphasized. This study empirically investigates the impact of the
Externí odkaz:
https://doaj.org/article/543da3ca0cc9466ba43e52ef06a8e2e5
Autor:
Haryanto, Christoforus Yoga, Elvira, Anne Maria, Nguyen, Trung Duc, Vu, Minh Hieu, Hartanto, Yoshiano, Lomempow, Emily, Arakala, Arathi
This paper surveys the potential of contextualized AI in enhancing cyber defense capabilities, revealing significant research growth from 2015 to 2024. We identify a focus on robustness, reliability, and integration methods, while noting gaps in orga
Externí odkaz:
http://arxiv.org/abs/2409.13524
Autor:
Vu Minh Hieu
Publikováno v:
International Journal of Energy Economics and Policy, Vol 12, Iss 3 (2022)
Currently, sustainable environment has become a global requirement due to the uncertainty of the environmental conditions and require researchers' and policymakers' attention. Therefore, the present research examines the role of green investment and
Externí odkaz:
https://doaj.org/article/65f0fefaa5a1468b937b92931227d4be
Autor:
Adamu Pantamee Abdurrahman, Shafi Mohamad, Amena Sibghatullah, Ooi Chee Keong, Vu Minh Hieu, Putri Mutira
Publikováno v:
International Journal of Energy Economics and Policy, Vol 12, Iss 3 (2022)
Recently, sustainable development goals (SDGs) have been the requirement of every organization around the globe that requires researchers and regulators' focus. Hence, the present study examines the impact of corporate social responsibilities (CSR) i
Externí odkaz:
https://doaj.org/article/9cd14b8df5df43d9897f13ce65692430
Autor:
Doan, Anh-Dzung, Phan, Vu Minh Hieu, Gupta, Surabhi, Wagner, Markus, Chin, Tat-Jun, Reid, Ian
Infrared imaging offers resilience against changing lighting conditions by capturing object temperatures. Yet, in few scenarios, its lack of visual details compared to daytime visible images, poses a significant challenge for human and machine interp
Externí odkaz:
http://arxiv.org/abs/2408.14227
Autor:
Chowdhury, Townim F., Phan, Vu Minh Hieu, Liao, Kewen, To, Minh-Son, Xie, Yutong, Hengel, Anton van den, Verjans, Johan W., Liao, Zhibin
The integration of vision-language models such as CLIP and Concept Bottleneck Models (CBMs) offers a promising approach to explaining deep neural network (DNN) decisions using concepts understandable by humans, addressing the black-box concern of DNN
Externí odkaz:
http://arxiv.org/abs/2408.02001
Autor:
Haryanto, Christoforus Yoga, Vu, Minh Hieu, Nguyen, Trung Duc, Lomempow, Emily, Nurliana, Yulia, Taheri, Sona
The rapid advancement of Generative AI (GenAI) technologies offers transformative opportunities within Australia's critical technologies of national interest while introducing unique security challenges. This paper presents SecGenAI, a comprehensive
Externí odkaz:
http://arxiv.org/abs/2407.01110
Autor:
Phan, Vu Minh Hieu, Xie, Yutong, Zhang, Bowen, Qi, Yuankai, Liao, Zhibin, Perperidis, Antonios, Phung, Son Lam, Verjans, Johan W., To, Minh-Son
Unpaired medical image synthesis aims to provide complementary information for an accurate clinical diagnostics, and address challenges in obtaining aligned multi-modal medical scans. Transformer-based models excel in imaging translation tasks thanks
Externí odkaz:
http://arxiv.org/abs/2406.18967
Autor:
Chowdhury, Townim Faisal, Liao, Kewen, Phan, Vu Minh Hieu, To, Minh-Son, Xie, Yutong, Hung, Kevin, Ross, David, Hengel, Anton van den, Verjans, Johan W., Liao, Zhibin
Deep Neural Networks (DNNs) are widely used for visual classification tasks, but their complex computation process and black-box nature hinder decision transparency and interpretability. Class activation maps (CAMs) and recent variants provide ways t
Externí odkaz:
http://arxiv.org/abs/2404.02388
Autor:
Phan, Vu Minh Hieu, Xie, Yutong, Qi, Yuankai, Liu, Lingqiao, Liu, Liyang, Zhang, Bowen, Liao, Zhibin, Wu, Qi, To, Minh-Son, Verjans, Johan W.
Publikováno v:
CVPR2024
Medical vision language pre-training (VLP) has emerged as a frontier of research, enabling zero-shot pathological recognition by comparing the query image with the textual descriptions for each disease. Due to the complex semantics of biomedical text
Externí odkaz:
http://arxiv.org/abs/2403.07636