H.R. Tizhoosh
Cited by
Cited by
Opposition-based learning: a new scheme for machine intelligence
HR Tizhoosh
International Conference on Computational Intelligence for Modelling …, 2005
Opposition-based differential evolution
S Rahnamayan, HR Tizhoosh, MMA Salama
IEEE Transactions on Evolutionary computation 12 (1), 64-79, 2008
Artificial Intelligence and Digital Pathology: Challenges and Opportunities
HR Tizhoosh, L Pantanowitz
Journal of Pathology Informatics 9 (38), 2018
Quasi-oppositional differential evolution
S Rahnamayan, HR Tizhoosh, MMA Salama
2007 IEEE congress on evolutionary computation, 2229-2236, 2007
A novel population initialization method for accelerating evolutionary algorithms
S Rahnamayan, HR Tizhoosh, MMA Salama
Computers & Mathematics with Applications 53 (10), 1605-1614, 2007
Opposition versus randomness in soft computing techniques
S Rahnamayan, HR Tizhoosh, MMA Salama
Applied Soft Computing 8 (2), 906-918, 2008
Image thresholding using type II fuzzy sets
HR Tizhoosh
Pattern recognition 38 (12), 2363-2372, 2005
Fuzzy image processing
HR Tizhoosh
Publisher: Springer-Verlag. Kartoniert (TB), Deutsch 10, 1997
Opposition-based differential evolution algorithms
S Rahnamayan, HR Tizhoosh, MMA Salama
2006 IEEE international conference on evolutionary computation, 2010-2017, 2006
Opposition-based reinforcement learning
HR Tizhoosh
Journal of Advanced Computational Intelligence and Intelligent Informatics …, 2006
Federated learning and differential privacy for medical image analysis
M Adnan, S Kalra, JC Cresswell, GW Taylor, HR Tizhoosh
Scientific reports 12 (1), 1953, 2022
Fuzzy image processing: an overview
HR Tizhoosh, H Haußecker
Handbook on Computer Vision and Applications 2, 683-727, 1999
Convolutional neural networks for histopathology image classification: Training vs. using pre-trained networks
B Kieffer, M Babaie, S Kalra, HR Tizhoosh
2017 seventh international conference on image processing theory, tools and …, 2017
Reinforcement learning based on actions and opposite actions
HR Tizhoosh
International conference on artificial intelligence and machine learning 414, 2005
Improving the convergence of backpropagation by opposite transfer functions
M Ventresca, HR Tizhoosh
The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006
Opposition-based differential evolution for optimization of noisy problems
S Rahnamayan, HR Tizhoosh, MMA Salama
2006 IEEE International Conference on Evolutionary Computation, 1865-1872, 2006
A comparative study of CNN, BoVW and LBP for classification of histopathological images
MD Kumar, M Babaie, S Zhu, S Kalra, HR Tizhoosh
2017 IEEE symposium series on computational intelligence (SSCI), 1-7, 2017
Ignorance functions. An application to the calculation of the threshold in prostate ultrasound images
H Bustince, M Pagola, E Barrenechea, J Fernández, P Melo-Pinto, ...
Fuzzy sets and Systems 161 (1), 20-36, 2010
Fine-tuning and training of densenet for histopathology image representation using tcga diagnostic slides
A Riasatian, M Babaie, D Maleki, S Kalra, M Valipour, S Hemati, M Zaveri, ...
Medical image analysis 70, 102032, 2021
Fast fuzzy edge detection
HR Tizhoosh
2002 Annual Meeting of the North American Fuzzy Information Processing …, 2002
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