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Fariborz Sobhanmanesh, Amin Beheshti, Nicholas Nouri, Natalia Monje Chapparo, Sandya Raj and Richard A. George
The widespread adoption of advanced technologies, such as Artificial Intelligence (AI), Machine Learning, and Robotics, is rapidly increasing across the globe. This accelerated pace of change is drastically transforming various aspects of our lives and w...
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Fariba Lotfi, Amin Beheshti, Helia Farhood, Matineh Pooshideh, Mansour Jamzad and Hamid Beigy
In our digital age, data are generated constantly from public and private sources, social media platforms, and the Internet of Things. A significant portion of this information comes in the form of unstructured images and videos, such as the 95 million d...
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Shuang Wang, Amin Beheshti, Yufei Wang, Jianchao Lu, Quan Z. Sheng, Stephen Elbourn and Hamid Alinejad-Rokny
Instructors face significant time and effort constraints when grading students? assessments on a large scale. Clustering similar assessments is a unique and effective technique that has the potential to significantly reduce the workload of instructors in...
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Amin Beheshti, Shahpar Yakhchi, Salman Mousaeirad, Seyed Mohssen Ghafari, Srinivasa Reddy Goluguri and Mohammad Amin Edrisi
Intelligence is the ability to learn from experience and use domain experts? knowledge to adapt to new situations. In this context, an intelligent Recommender System should be able to learn from domain experts? knowledge and experience, as it is vital to...
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Huan Niu, Nasim Khozouie, Hamid Parvin, Hamid Alinejad-Rokny, Amin Beheshti and Mohammad Reza Mahmoudi
Clustering ensemble indicates to an approach in which a number of (usually weak) base clusterings are performed and their consensus clustering is used as the final clustering. Knowing democratic decisions are better than dictatorial decisions, it seems c...
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