| Covid-caps: A capsule network-based framework for identification of covid-19 cases from x-ray images P Afshar, S Heidarian, F Naderkhani, A Oikonomou, KN Plataniotis, ... Pattern Recognition Letters 138, 638-643, 2020 | 727 | 2020 |
| Brain tumor type classification via capsule networks P Afshar, A Mohammadi, KN Plataniotis 2018 25th IEEE international conference on image processing (ICIP), 3129-3133, 2018 | 526 | 2018 |
| Capsule networks for brain tumor classification based on MRI images and coarse tumor boundaries P Afshar, KN Plataniotis, A Mohammadi ICASSP 2019-2019 IEEE international conference on acoustics, speech and …, 2019 | 339 | 2019 |
| From handcrafted to deep-learning-based cancer radiomics: challenges and opportunities P Afshar, A Mohammadi, KN Plataniotis, A Oikonomou, H Benali IEEE Signal Processing Magazine 36 (4), 132-160, 2019 | 295 | 2019 |
| COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning P Afshar, S Heidarian, N Enshaei, F Naderkhani, MJ Rafiee, ... Scientific Data 8 (1), 121, 2021 | 187 | 2021 |
| Improved explainability of capsule networks: Relevance path by agreement A Shahroudnejad, P Afshar, KN Plataniotis, A Mohammadi 2018 IEEE global conference on signal and information processing (GlobalSIP …, 2018 | 86 | 2018 |
| Bayescap: A bayesian approach to brain tumor classification using capsule networks P Afshar, A Mohammadi, KN Plataniotis IEEE Signal Processing Letters 27, 2024-2028, 2020 | 69 | 2020 |
| Covid-fact: A fully-automated capsule network-based framework for identification of covid-19 cases from chest ct scans S Heidarian, P Afshar, N Enshaei, F Naderkhani, MJ Rafiee, ... Frontiers in Artificial Intelligence 4, 598932, 2021 | 60 | 2021 |
| 3D-MCN: a 3D multi-scale capsule network for lung nodule malignancy prediction P Afshar, A Oikonomou, F Naderkhani, PN Tyrrell, KN Plataniotis, ... Scientific reports 10 (1), 7948, 2020 | 57 | 2020 |
| MIXCAPS: A capsule network-based mixture of experts for lung nodule malignancy prediction P Afshar, F Naderkhani, A Oikonomou, MJ Rafiee, A Mohammadi, ... Pattern Recognition 116, 107942, 2021 | 50 | 2021 |
| : deep learning-based radiomics for the time-to-event outcome prediction in lung cancer P Afshar, A Mohammadi, PN Tyrrell, P Cheung, A Sigiuk, KN Plataniotis, ... Scientific Reports 10 (1), 12366, 2020 | 37 | 2020 |
| Intelligent breast cancer recognition using particle swarm optimization and support vector machines A Ahmadi, P Afshar Journal of Experimental & Theoretical Artificial Intelligence 28 (6), 1021-1034, 2016 | 37 | 2016 |
| Ct-caps: Feature extraction-based automated framework for covid-19 disease identification from chest ct scans using capsule networks S Heidarian, P Afshar, A Mohammadi, MJ Rafiee, A Oikonomou, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 30 | 2021 |
| Capsule networks’ interpretability for brain tumor classification via radiomics analyses P Afshar, KN Plataniotis, A Mohammadi 2019 IEEE International Conference on Image Processing (ICIP), 3816-3820, 2019 | 26 | 2019 |
| COVID-rate: an automated framework for segmentation of COVID-19 lesions from chest CT images N Enshaei, A Oikonomou, MJ Rafiee, P Afshar, S Heidarian, ... Scientific Reports 12 (1), 3212, 2022 | 24 | 2022 |
| Human-level COVID-19 diagnosis from low-dose CT scans using a two-stage time-distributed capsule network P Afshar, MJ Rafiee, F Naderkhani, S Heidarian, N Enshaei, ... Scientific Reports 12 (1), 4827, 2022 | 22 | 2022 |
| BoostCaps: a boosted capsule network for brain tumor classification P Afshar, KN Plataniotis, A Mohammadi 2020 42nd annual international conference of the IEEE engineering in …, 2020 | 21 | 2020 |
| Lung cancer radiomics: highlights from the ieee video and image processing cup 2018 student competition [sp competitions] A Mohammadi, P Afshar, A Asif, K Farahani, J Kirby, A Oikonomou, ... IEEE signal processing magazine 36 (1), 164-173, 2018 | 20 | 2018 |
| Diagnosis/prognosis of covid-19 chest images via machine learning and hypersignal processing: Challenges, opportunities, and applications A Mohammadi, Y Wang, N Enshaei, P Afshar, F Naderkhani, ... IEEE Signal Processing Magazine 38 (5), 37-66, 2021 | 19 | 2021 |
| Lung tumor area recognition in CT images based on Gustafson-Kessel clustering P Afshar, A Ahmadi, MHF Zarandi 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2302-2308, 2016 | 15 | 2016 |
Arash MohammadiAssociate Professor, Concordia University在 encs.concordia.ca 的电子邮件经过验证
