An LSTM Network for Highway Trajectory Prediction
Impact in
Classified as
- Journal
- arXiv (Cornell University)
In The Last Decade
doi.org/w29324683 →Countries where authors are citing An LSTM Network for Highway Trajectory Prediction
This map shows the geographic impact of An LSTM Network for Highway Trajectory Prediction. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by An LSTM Network for Highway Trajectory Prediction with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites An LSTM Network for Highway Trajectory Prediction more than expected).
Fields of papers citing An LSTM Network for Highway Trajectory Prediction
This network shows the impact of An LSTM Network for Highway Trajectory Prediction. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the An LSTM Network for Highway Trajectory Prediction.
About An LSTM Network for Highway Trajectory Prediction
This paper, published in 2018, received 440 indexed citations . Written by Florent Altché and Arnaud de La Fortelle covering the research area of Building and Construction, Automotive Engineering and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Automotive Engineering (276 citations), Building and Construction (176 citations), Computer Vision and Pattern Recognition (114 citations), Control and Systems Engineering (91 citations) and Safety, Risk, Reliability and Quality (90 citations). Published in arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w29324683.