TSI Researchers continue to be in the top! This time, a new paper of TSI researcher, Dr. Dmitry Pavlyuk, has been published in a peer-reviewed open access journal Algorithms (ISSN 1999-4893). The paper is titled “Transfer Learning: Video Prediction and Spatiotemporal Urban Traffic Forecasting” and devoted to transferring of video prediction models into urban traffic forecasting context. Taking into account high quality of the paper and actuality of the discussed topic, the study was selected as a front page of the forthcoming issue of Algorithms and placed on the issue cover.
Short paper abstract:
Transfer learning is a modern concept that focuses on the application of ideas, models, and algorithms, developed in one applied area, for solving a similar problem in another area. In this paper, we identify links between methodologies in two fields: video prediction and spatiotemporal traffic forecasting. The similarities of the video stream and citywide traffic data structures are discovered and analogues between historical development and modern states of the methodologies are presented and discussed. The idea of transferring video prediction models to the urban traffic forecasting domain is validated using a large real-world traffic data set. We conclude that the application of video prediction models and algorithms for urban traffic forecasting is effective both in terms of observed forecasting accuracy and development, and training efforts.
We congratulate Dr. D. Pavlyuk with yet another excellent accomplishment
and welcome everyone to learn more about the results of his research by reading an article here.