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Artificial intelligence and robotics: Great expectations and daunting existential risks -Newsday Zimbabwe - Vimarsana News

Artificial intelligence and robotics: Great expectations and daunting existential risks -Newsday Zimbabwe

This capability is in contrast to the natural intelligence manifested by humans and other animals.

The Decade of Deep Learning - Vimarsana News

The Decade of Deep Learning

As the 2010’s draw to a close, it’s worth taking a look back at the monumental progress that has been made in Deep Learning in this decade.[1] Driven by the development of ever-more powerful comput

Source: bmk.sh
Looking For A Ph.D. In Physics Or Computer Science? Look No Further - Vimarsana News

Looking For A Ph.D. In Physics Or Computer Science? Look No Further

Today the University of Padova has issued a call for Ph. D. positions to start in October 2021, and the Department of Physics and Astronomy has 23 new openings. The English version of the call page is here.

"Contrastive Positive Mining for Unsupervised 3D Action Representation " by Haoyuan Zhang, Yonghong Hou et al. - Vimarsana News

"Contrastive Positive Mining for Unsupervised 3D Action Representation " by Haoyuan Zhang, Yonghong Hou et al.

Recent contrastive based 3D action representation learning has made great progress. However, the strict positive/negative constraint is yet to be relaxed and the use of non-self positive is yet to be explored. In this paper, a Contrastive Positive Mining (CPM) framework is proposed for unsupervised skeleton 3D action representation learning. The CPM identifies non-self positives in a contextual queue to boost learning. Specifically, the siamese encoders are adopted and trained to match the similarity distributions of the augmented instances in reference to all instances in the contextual queue...

Source: uow.edu.au
"Unsupervised Learning Composite Network to Reduce Training Cost of Dee" by Jirui Guo, Wuteng Cao et al. - Vimarsana News

"Unsupervised Learning Composite Network to Reduce Training Cost of Dee" by Jirui Guo, Wuteng Cao et al.

Deep learning facilitates complex medical data analysis and is increasingly being explored in colorectal cancer diagnostics. However, the training cost of the deep learning model limits its real-world medical utility. In this study, we present a composite network that combines deep learning and unsupervised K-means clustering algorithm (RK-net) for automatic processing of medical images. RK-net was more efficient in image refinement compared with manual screening and annotation. The training of a deep learning model for colorectal cancer diagnosis was accelerated by two times with utilization ...

Source: uow.edu.au