Books:

1. A. Vakanski, and F. Janabi-Sharifi, Robot Learning by Visual Observation, John Wiley & Sons, Inc., 208 pages, ISBN-10: 1119091802, ISBN-13: 978-1119091806, 2017. [Amazon] [Wiley]

 

Journal publications:

1. B. Zhang, A. Vakanski and M. Xian, "BI-RADS-NET-V2: A composite multi-task neural network for computer-aided diagnosis of breast cancer in ultrasound images with semantic and quantitative explanations," IEEE Access, vol. 11, pp. 79480–79494, Jul. 2023. [DOI: 10.1109/ACCESS.2023.3298569] [Bibtex] [IEEE Explore] 

2. F. Alharbi, and A. Vakanski, "Machine Learning methods for cancer classification using gene expression data: A review," Bioengineering, vol. 10, no. 2, pp. 1–26, Jan. 2023. [DOI: 10.3390/bioengineering10020173] [Bibtex] [MDPI Bioengineering] 

3. B. Shareef, A. Vakanski, P. E. Freer, and M. Xian, "ESTAN: Enhanced small tumor-aware network for breast ultrasound image segmentation," Healthcare, vol. 10, no. 11, pp. 1–14, Nov. 2022. [DOI: 10.3390/healthcare10112262] [Bibtex] [MDPI Healthcare] 

4. S. Butte, A. Vakanski, K. Duellman, H. Wang, and A. Mirkouei, "Potato crop stress identification in aerial images using deep learning-based object detection," Agronomy Journal, vol. 113, no. 5, pp. 3991–4002, Sep. 2021. [DOI: 10.1002/agj2.20841] [Bibtex] [Wiley Online Library]  

5. A. Vakanski, M. Xian, and P. Freer, "Attention enriched deep learning model for breast tumor segmentation in ultrasound images," Ultrasound in Medicine and Biology, vol. 46, no. 10, pp. 2819–2833, Oct. 2020. [DOI: 10.1016/j.ultrasmedbio.2020.06.015] [PMCID: PMC7483681] [Bibtex] [Elsevier Science Direct] 

6. Y. Liao, A. Vakanski, M. Xian, D. Paul, and R. Baker, "A review of computational approaches for evaluation of rehabilitation exercises," Computers in Biology and Medicine, vol. 119, article no. 103687, Apr. 2020. [DOI: 10.1016/j.compbiomed.2020.103687] [PMCID: PMC7189627] [Bibtex] [Elsevier Science Direct] 

7. Y. Liao, A. Vakanski, and M. Xian, "A deep learning framework for assessing physical rehabilitation exercises," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 2, pp. 468–477, Feb. 2020. [DOI: 10.1109/TNSRE.2020.2966249] [PMCID: PMC7032994] [Bibtex] [IEEE Explore] 

8. C. Williams, A. Vakanski, S. Lee, and D. Paul, "Assessment of physical rehabilitation movements through dimensionality reduction and statistical modeling," Medical Engineering & Physics, vol. 74, pp. 13–22, Dec. 2019. [DOI: 10.1016/j.medengphy.2019.10.003] [PMCID: PMC6875616] [Bibtex] [Elsevier Science Direct] 

9. R. E. Hiromoto, M Haney, A. Vakanski, and B. Shareef, "Toward a secure IoT architecture," Advanced Control Techniques in Complex Engineering Systems: Theory and Applications, Springer's book: Studies in Systems, Decision and Control, vol. 203, pp. 297–323, May 2019. [DOI: 10.1007/978-3-030-21927-7_14] [Bibtex] [Springer Link]

10. L. Li, and A. Vakanski, "Generative adversarial networks for generation and classification of physical rehabilitation movement episodes," International Journal of Machine Learning and Computing, vol. 8, no. 5, pp. 428–436, Oct. 2018. [DOI: 10.18178/ijmlc.2018.8.5.724] [PMCID: PMC6195368] [Bibtex] [IJMLC] 

11. A. Vakanski, H-p. Jun, D. Paul, and R. Baker, "A data set of human body movements for physical rehabilitation exercises," Data, vol. 3, no. 2, pp. 1–15, Jan. 2018. [DOI: 10.3390/data3010002] [PMCID: PMC6195368] [Bibtex] [MDPI Data] 

12. A. Vakanski, F. Janabi-Sharifi, and I. Mantegh, "An image-based trajectory planning approach for robust robot programming by demonstration," Robotics and Autonomous Systems, vol. 98, pp. 241–257, Dec. 2017. [DOI: 10.1016/j.robot.2017.09.012] [Bibtex] [Elsevier Science Direct] 

13. A. Vakanski, J. M. Ferguson, and S. Lee, "Metrics for performance evaluation of patient exercises during physical therapy," International Journal of Physical Medicine and Rehabilitation, vol. 5, no. 3, pp. 1–6, Jun. 2017. [DOI: 10.4172/2329-9096.1000403] [PMCID: PMC5526359] [Bibtex] [Int. J. Phys. Med. Rehabil.] 

14. A. Vakanski, J. M. Ferguson, and S. Lee, "Mathematical modeling and evaluation of human motions in physical therapy using mixture density neural networks," Journal of Physiotherapy and Physical Rehabilitation, vol. 1, no. 4, pp. 1–10, Dec. 2016. [DOI: 10.4172/2573-0312.1000118] [PMCID: PMC5242735] [Bibtex] [Physiother. Rehabil.] 

15. A. Vakanski, F. Janabi-Sharifi, and I. Mantegh, "Robotic learning of manipulation tasks from visual perception using a Kinect sensor," International Journal of Machine Learning and Computing, vol. 4, no. 2, pp. 163–169, Apr. 2014. [DOI: 10.7763/IJMLC.2014.V4.406] [Bibtex] [IJMLC]

16. A. Vakanski, I. Mantegh, A. Irish, and F. Janabi-Sharifi, "Trajectory learning for robot programming by demonstration using Hidden Markov Model and Dynamic Time Warping," IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, vol. 42, no. 4, pp. 1039–1052, Aug. 2012. [DOI: 10.1109/TSMCB.2012.2185694] [BibTex] [IEEE Explore]

17. E. Nematollahi, A. Vakanski, and F. Janabi-Sharifi, "A second-order conic optimization-based method for visual servoing," Journal of Mechatronics, vol. 22, no. 4, pp. 444–467, Jun. 2012. [DOI: 10.1016/j.mechatronics.2012.01.010] [BibTex] [Mechatronics]

18. F. Janabi-Sharifi, and Vakanski, "Analysis of visual acuity and motion resolvability as measures for optimal visual perception of the workspace," Applied Ergonomics, vol. 42, no. 3, pp. 473–486, Mar. 2011. [DOI: 10.1016/j.apergo.2010.09.008] [BibTex] [Applied Ergonomics]

 

Conference publications:

1. M. Karimzadeh, A. Vakanski, M. Xian, and B. Zhang, "Post-hoc explainability of BI-RADS descriptors in a multi-task framework for breast cancer detection and segmentation," in Proceedings of the 33rd IEEE International Workshop on Machine Learning and Signal Processing (MLSP 2023), Rome, Italy, pp. 1-6, 2023. [DOI: 10.1109/MLSP55844.2023.10286006] [BibTex] [IEEE Explore] 

2. B. Shareef, M. Xian, A. Vakanski, and H. Wang, "Breast ultrasound tumor classification using a hybrid multitask CNN-transformer network," in Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2023), Vancouver, Canada, pp. 344-353, 2023. [DOI: 10.1007/978-3-031-43901-8_33] [BibTex] [Springer Link] 

3. H. Wang, M. Xian, A. Vakanski, and B. Shareef, "SIAN: Style-guided instance-adaptive normalization for multi-organ histopathology image synthesis," in Proceedings of the International Symposium on Biomedical Imaging (ISBI 2023), Cartagena de Indias, Colombia, pp. 1-5, 2023. [DOI: 10.1109/ISBI53787.2023.10230507]

4. S. Butte, H. Wang, A. Vakanski, and M. Xian, "Enhanced Sharp-GAN for histopathology image synthesis," in Proceedings of the International Symposium on Biomedical Imaging (ISBI 2023), Cartagena de Indias, Colombia, pp. 1-5, 2023. [DOI: 10.1109/ISBI53787.2023.10230516]

5. S. Sun, M. Xian, A. Vakanski, and H. Ghanem, "MIRST-DM: Multi-instance RST with drop-max layer for robust classification of breast cancer," in Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022), Singapore, Singapore, pp. 401-410, 2022. [DOI: 10.1007/978-3-031-16440-8_39] [BibTex] [Springer Link] 

6. J. Shi, A. Vakanski, M. Xian, J. Ding, and C. Ning, "EMT-Net: Efficient multitask network for computer-aided diagnosis of breast cancer," in Proceedings of the International Symposium on Biomedical Imaging (ISBI 2022), Kolkata, India, pp. 1-5, 2022. [DOI: 10.1109/ISBI52829.2022.9761438] [PMCID: PMC9074851] [BibTex] [IEEE Explore] 

7. S. Butte, H. Wang, M. Xian, and A. Vakanski, "Sharp-GAN: Sharpness loss regularized GAN for histopathology image synthesis," in Proceedings of the International Symposium on Biomedical Imaging (ISBI 2022), Kolkata, India, pp. 1-5, 2022. [DOI: 10.1109/ISBI52829.2022.9761534] [PMCID: PMC9074846] [BibTex] [IEEE Explore] 

8. H. Wang, M. Xian, and A. Vakanski, "TA-Net: Topology-aware network for gland segmentation," in Proceedings of the Winter Conference on Applications of Computer Vision (WACV 2022), Waikoloa, USA, pp. 1556-1564, 2022. [PMCID: PMC9063467] [BibTex] [WACV 2022 Open Access] 

9. B. Zhang, A. Vakanski, and M. Xian, "BI-RADS-Net: An explainable multitask learning approach for cancer diagnosis in breast ultrasound images," in Proceedings of the 31st IEEE International Workshop on Machine Learning and Signal Processing (MLSP 2021), Gold Coast, Australia, pp. 1-6, 2021. [DOI: 10.1109/MLSP52302.2021.9596314] [PMCID: PMC9063460] [BibTex] [IEEE Explore] 

10. A. Vakanski, and M. Xian, "Evaluation of complexity measures for deep learning generalization in medical image analysis," in Proceedings of the 31st IEEE International Workshop on Machine Learning and Signal Processing (MLSP 2021), Gold Coast, Australia, pp. 1-6, 2021. [DOI: 10.1109/MLSP52302.2021.9596501] [PMCID: PMC9071170] [BibTex] [IEEE Explore] 

11. H. Wang, M. Xian, and A. Vakanski, "Bending loss regularized network for nuclei segmentation in histopathology images," in Proceedings of the 17th IEEE International Symposium on Biomedical Imaging (ISBI 2020), Iowa City, USA, pp. 1-5, 2020. [DOI: 10.1109/ISBI45749.2020.9098611] [PMCID: PMC7733529] [BibTex] [IEEE Explore]  

12. B. Shareef, M. Xian, and A. Vakanski, "STAN: Small tumor-aware network for breast ultrasound image segmentation," in Proceedings of 17th IEEE the International Symposium on Biomedical Imaging (ISBI 2020), Iowa City, USA, pp. 1-5, 2020. [DOI: 10.1109/ISBI45749.2020.9098691] [PMCID: PMC7733528] [BibTex] [IEEE Explore]  

13. S. Butte, A. Vakanski, and M. Xian, "Deep learning for industrial IoT-empowered processes: Methods, applications, infrastructure, and practical considerations," in Proceedings of the IEEE Workshop on Microelectronics and Electron Devices, Boise, USA, pp. 1-5, 2019.

14. M. Ghahramani, A. Vakanski, and F. Janabi-Sharifi, "6D object pose estimation for robot programming by demonstration," in Proceedings of the International Symposium on Optomechatronic Technologies, Cancun, Mexico, pp. 1–6, 2018. [DOI: 10.1007/978-981-32-9632-9_11] [BibTex] [Springer Link]

15. R. E. Hiromoto, M. Haney, and A. Vakanski, "A secure architecture for IoT with supply chain risk management," in Proceedings of the IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, Bucharest, Romania, pp. 1–6, 2017. [DOI: 10.1109/IDAACS.2017.8095118] [BibTex] [IEEE Explore]

16. A. Vakanski, F. Janabi-Sharifi, and I. Mantegh, "Transferring skills to robots for tasks with cyclic motions via dynamical systems approach," in Proceedings of the International Symposium on Optomechatronic Technologies, Paris, France, pp. 1–6, 2012. [DOI: 10.1109/ISOT.2012.6403253] [BibTex] [IEEE Explore]

17. A. Vakanski, F. Janabi-Sharifi, I. Mantegh, and A. Irish, "Trajectory learning based on Conditional Random Fields for robot programming by demonstration," in Proceedings of the IASTED International Conference on Robotics and Applications, Cambridge, USA, pp. 401–408, 2010. [DOI: 10.2316/P.2010.706-061] [BibTex] [IASTED]

18. A. Vakanski, A. Tuneski, and D. Babunski, "Design of digital control using frequency response methods," in Proceedings of the Third International Conference on Applied Automatic Systems, Ohrid, Macedonia, pp. 283–289, 2003.

19. A. Vakanski, A. Tuneski, and D. Babunski, "Time-optimal control of non-linear discrete systems," in Proceedings of the Third International Conference on Applied Automatic Systems, Ohrid, Macedonia, pp. 187–193, 2003.

 

Patents:

1. A. Vakanski, and F. Janabi-Sharifi, Image-based Trajectory Robot Programming Planning Approach, U.S. Patent 10,112,303 (filed Aug. 25, 2016, granted Oct. 30, 2018). Based on International Patent Application PCT/CA2014/051016 (Oct. 2014). [U.S. Patent 10,112,303]

2. A. Vakanski, and F. Janabi-Sharifi, Image-based Robot Trajectory Planning Approach, Canada Patent 2,928,645 (filed Apr. 20, 2015, granted Oct. 26, 2021). Based on International Patent Application PCT/CA2014/051016 (Oct. 2014). [Canada Patent 2,928,645]