1 code implementation • 26 Jul 2023 • Milad Abdollahzadeh, Touba Malekzadeh, Christopher T. H. Teo, Keshigeyan Chandrasegaran, Guimeng Liu, Ngai-Man Cheung
In machine learning, generative modeling aims to learn to generate new data statistically similar to the training data distribution.
no code implementations • 4 Jul 2023 • Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Chao Du, Tianyu Pang, Ruoteng Li, Henghui Ding, Ngai-Man Cheung
However, a major limitation of existing methods is that their knowledge preserving criteria consider only source domain/task and fail to consider target domain/adaptation in selecting source knowledge, casting doubt on their suitability for setups of different proximity between source and target domain.
1 code implementation • CVPR 2023 • Yunqing Zhao, Chao Du, Milad Abdollahzadeh, Tianyu Pang, Min Lin, Shuicheng Yan, Ngai-Man Cheung
To this end, we propose knowledge truncation to mitigate this issue in FSIG, which is a complementary operation to knowledge preservation and is implemented by a lightweight pruning-based method.
1 code implementation • CVPR 2023 • Ngoc-Bao Nguyen, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man Cheung
Recently, several algorithms for MI have been proposed to improve the attack performance.
1 code implementation • 2 Dec 2022 • Christopher TH Teo, Milad Abdollahzadeh, Ngai-Man Cheung
We find that our fairTL can learn expressive sample generation during pre-training, thanks to the large (biased) dataset.
2 code implementations • 29 Oct 2022 • Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man Cheung
However, a major limitation of existing methods is that their knowledge preserving criteria consider only source domain/source task, and they fail to consider target domain/adaptation task in selecting source model's knowledge, casting doubt on their suitability for setups of different proximity between source and target domain.
Ranked #1 on 10-shot image generation on Babies
1 code implementation • NeurIPS 2021 • Milad Abdollahzadeh, Touba Malekzadeh, Ngai-Man Cheung
Second, inspired by hard parameter sharing in multi-task learning and a new interpretation of related work, we propose a new multimodal meta-learner that outperforms existing work by considerable margins.
no code implementations • 28 Sep 2020 • Milad Abdollahzadeh, Touba Malekzadeh, Hadi Seyedarabi
Image fusion in visual sensor networks (VSNs) aims to combine information from multiple images of the same scene in order to transform a single image with more information.
no code implementations • 25 Sep 2020 • Hamdollah Nasrollahi, Kamran Farajzadeh, Vahid Hosseini, Esmaeil Zarezadeh, Milad Abdollahzadeh
In this way, we are able to use the ground-truth images as target and avoid misleading the network due to artifacts in difference image.
no code implementations • 28 Feb 2018 • Hossein Nejati, Hamed Alizadeh Ghazijahani, Milad Abdollahzadeh, Tooba Malekzadeh, Ngai-Man Cheung, Kheng Hock Lee, Lian Leng Low
In particular, seemingly, all previous approaches have assumed only 3 tissue types in the chronic wounds, while these wounds commonly exhibit 7 distinct tissue types that presence of each one changes the treatment procedure.
no code implementations • 26 Dec 2017 • Touba Malekzadeh, Milad Abdollahzadeh, Hossein Nejati, Ngai-Man Cheung
To ensure flight safety of aircraft structures, it is necessary to have regular maintenance using visual and nondestructive inspection (NDI) methods.