12 citations · 23 across the 4 of their papers we have counts for
5 papers
Fair Generative Models via Transfer Learning
Christopher TH Teo, Milad Abdollahzadeh, Ngai-Man Cheung
This work addresses fair generative models. Dataset biases have been a major cause of unfairness in deep generative models. Previous work had proposed to augment large, biased data…
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning
Milad Abdollahzadeh, Touba Malekzadeh, Ngai-Man Cheung
Multimodal meta-learning is a recent problem that extends conventional few-shot meta-learning by generalizing its setup to diverse multimodal task distributions. This setup makes a…
Multi-focus Image Fusion for Visual Sensor Networks
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. Image f…
Deep Artifact-Free Residual Network for Single Image Super-Resolution
Hamdollah Nasrollahi, Kamran Farajzadeh, Vahid Hosseini +2
Recently, convolutional neural networks have shown promising performance for single-image super-resolution. In this paper, we propose Deep Artifact-Free Residual (DAFR) network whi…
Fine-grained wound tissue analysis using deep neural network
Hossein Nejati, Hamed Alizadeh Ghazijahani, Milad Abdollahzadeh +4
Tissue assessment for chronic wounds is the basis of wound grading and selection of treatment approaches. While several image processing approaches have been proposed for automatic…