A SVM-based model-transferring method for heterogeneous domain adaptation AS Mozafari, M Jamzad Pattern Recognition 56, 142-158, 2016 | 52 | 2016 |
Attended temperature scaling: a practical approach for calibrating deep neural networks AS Mozafari, HS Gomes, W Leão, S Janny, C Gagné arXiv preprint arXiv:1810.11586, 2018 | 34* | 2018 |
Training my car to see using virtual worlds AM López, G Villalonga, L Sellart, G Ros, D Vázquez, J Xu, J Marin, ... Image and Vision Computing 68, 102-118, 2017 | 18 | 2017 |
Diversity regularization in deep ensembles C Shui, AS Mozafari, J Marek, I Hedhli, C Gagné arXiv preprint arXiv:1802.07881, 2018 | 17 | 2018 |
Controlling over-generalization and its effect on adversarial examples generation and detection M Abbasi, A Rajabi, AS Mozafari, RB Bobba, C Gagne arXiv preprint arXiv:1808.08282, 2018 | 8 | 2018 |
Cluster-based adaptive SVM: A latent subdomains discovery method for domain adaptation problems AS Mozafari, M Jamzad Computer Vision and Image Understanding 162, 116-134, 2017 | 7 | 2017 |
Heterogeneous domain adaptation using previously learned classifier for object detection problem AS Mozafari, M Jamzad 2014 IEEE International Conference on Image Processing (ICIP), 4077-4081, 2014 | 5 | 2014 |
A new type of hybrid features for human detection AS Mozafari, M Jamzad 2012 IEEE 8th International Conference on Intelligent Computer Communication …, 2012 | 3 | 2012 |
Unsupervised Temperature Scaling: Post-Processing Unsupervised Calibration of Deep Models Decisions AS Mozafari, HS Gomes, W Leão, C Gagné ICML 2019 Workshop on Uncertainty and Robustness in Deep Learning, 2019 | 2 | 2019 |
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift AS Mozafari, HS Gomes, C Gagné http://arxiv.org/abs/1911.11195, 2019 | 1 | 2019 |
Node-Adapt, Path-Adapt and Tree-Adapt: Model-Transfer Domain Adaptation for Random Forest AS Mozafari, D Vazquez, M Jamzad, AM Lopez arXiv preprint arXiv:1611.02886, 2016 | 1 | 2016 |