Imidazolinium based porous hypercrosslinked ionic polymers.
Applications of Deep Learning to MRI Images: A Survey. Abstract—Deep learning is providing exciting solutions for the problems in image recognition, speech recognition and natural language processing, and is seen as a key method for future various applications.Duing to non-invasive imaging and good soft tissue contrast of magnetic resonance imaging (MRI) images, MRI images are attracting.
Kim Hazelwood, Sarah Bird, David Brooks, Soumith Chintala, Utku Diril, Dmytro Dzhulgakov, Mohamed Fawzy, Bill Jia, Yangqing Jia, Aditya Kalro, et al. 2018. Applied machine learning at Facebook: A datacenter infrastructure perspective. In 2018 IEEE International Symposium on High Performance Computer Architecture (HPCA). Google Scholar Cross Ref.
Improving road safety is critical for the sustainable development of cities. A road safety map is a powerful tool that can help prevent future traffic accidents. However, accurate mapping requires accurate data collection, which is both expensive and labor intensive. Satellite imagery is increasingly becoming abundant, higher in resolution and affordable.
Jia Deng. PhD Dissertation 2012 ( pdf) Hedging Your Bets: Optimizing Accuracy-Specificity Trade-offs in Large Scale Visual Recognition Jia Deng, Jonathan Krause, Alex Berg, Li Fei-Fei IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2012. ( paper) ( supplementary materials) ( code) ( project site) ( bibtex).
You can write a book review and share your experiences. Other readers will always be interested in your opinion of the books you've read. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them.
In this dissertation, we study visual analysis methods for complex ancient Maya writings. The unit sign of a Maya text is called glyph, and may have either semantic or syllabic significance. There are over 800 identified glyph categories, and over 1400 variations across these categories. To enable fast manipulation of data by scholars in Humanities, it is desirable to have automatic visual.
We present OpenFace, our new open-source face recognition system that approaches state-of-the-art accuracy. Integrating OpenFace with inter-frame tracking, we build RTFace, a mechanism for denaturing video streams that selectively blurs faces according to specified policies at full frame rates.