Saeid Asgari
Saeid Asgari
Autodesk AI Research
Verified email at - Homepage
Cited by
Cited by
Deep semantic segmentation of natural and medical images: a review
S Asgari Taghanaki, K Abhishek, JP Cohen, J Cohen-Adad, G Hamarneh
Artificial Intelligence Review 54, 137-178, 2021
Combo loss: Handling input and output imbalance in multi-organ segmentation
SA Taghanaki, Y Zheng, SK Zhou, B Georgescu, P Sharma, D Xu, ...
Computerized Medical Imaging and Graphics 75, 24-33, 2019
Vulnerability analysis of chest X-ray image classification against adversarial attacks
S Asgari Taghanaki, A Das, G Hamarneh
Understanding and Interpreting Machine Learning in Medical Image Computing …, 2018
Understanding and interpreting machine learning in medical image computing applications
D Stoyanov, Z Taylor, SM Kia, I Oguz, M Reyes, A Martel, L Maier-Hein, ...
Springer International Publishing, 2018
Geometry-based pectoral muscle segmentation from MLO mammogram views
SA Taghanaki, Y Liu, B Miles, G Hamarneh
IEEE Transactions on Biomedical Engineering 64 (11), 2662-2671, 2017
InfoMask: Masked Variational Latent Representation to Localize Chest Disease
SA Taghanaki, M Havaei, T Berthier, F Dutil, L Di Jorio, G Hamarneh, ...
MICCAI 2019, 2019
Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification
SA Taghanaki, J Kawahara, B Miles, G Hamarneh
Computer methods and programs in biomedicine 145, 85-93, 2017
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
SA Taghanaki, K Abhishek, S Azizi, G Hamarneh
CVPR 2019, 2019
Select, attend, and transfer: Light, learnable skip connections
SA Taghanaki, A Bentaieb, A Sharma, SK Zhou, Y Zheng, B Georgescu, ...
MICCAI 2019, 2019
RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers
SA Taghanaki, J Luo, R Zhang, Y Wang, PK Jayaraman, ...
ICLR 2021, RobustML, 2021
Segmentation-free direct tumor volume and metabolic activity estimation from PET scans
SA Taghanaki, N Duggan, H Ma, X Hou, A Celler, F Benard, G Hamarneh
Computerized Medical Imaging and Graphics 63, 52-66, 2018
Robust Representation Learning via Perceptual Similarity Metrics
SA Taghanaki, K Choi, A Khasahmadi, A Goyal
ICML 2021, 2021
Nonlinear feature transformation and genetic algorithm-based feature selection: improving system security and decreasing computational cost
SA Taghanaki, MR Ansari, BZ Dehkordi, SA Mousavi
ETRI Journal 34 (6), 847-857, 2012
Masktune: Mitigating spurious correlations by forcing to explore
S Asgari, A Khani, F Khani, A Gholami, L Tran, A Mahdavi Amiri, ...
NeurIPS 2022, 2022
PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing
SA Taghanaki, K Hassani, PK Jayaraman, AH Khasahmadi, T Custis
ICML 2020, Human Interpretability in Machine Learning (WHI), 2020
Jigsaw-vae: Towards balancing features in variational autoencoders
SA Taghanaki, M Havaei, A Lamb, A Sanghi, A Danielyan, T Custis
arXiv preprint arXiv:2005.05496, 2020
Improved Inference via Deep Input Transfer
SA Taghanaki, K Abhishek, G Hamarneh
MICCAI 2019, 2019
Sketch-a-shape: Zero-shot sketch-to-3d shape generation
A Sanghi, PK Jayaraman, A Rampini, J Lambourne, H Shayani, ...
arXiv preprint arXiv:2307.03869, 2023
Slime: Segment like me
A Khani, SA Taghanaki, A Sanghi, AM Amiri, G Hamarneh
ICLR 2024, 2023
Weakly-Supervised Group Disentanglement using Total Correlation
L Tran, SA Taghanaki, AH Khasahmadi, A Sanghi
ICLR 2021 Workshop on Weakly Supervised Learning (WeaSuL), 2021
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