Yale Song

40 papers and 1.6k indexed citations i.

About

Yale Song is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Yale Song has authored 40 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computer Vision and Pattern Recognition, 21 papers in Artificial Intelligence and 11 papers in Signal Processing. Recurrent topics in Yale Song’s work include Human Pose and Action Recognition (17 papers), Multimodal Machine Learning Applications (17 papers) and Domain Adaptation and Few-Shot Learning (10 papers). Yale Song is often cited by papers focused on Human Pose and Action Recognition (17 papers), Multimodal Machine Learning Applications (17 papers) and Domain Adaptation and Few-Shot Learning (10 papers). Yale Song collaborates with scholars based in United States, United Kingdom and South Korea. Yale Song's co-authors include Randall Davis, Shuang Ma, Daniel McDuff, Gunhee Kim and Louis–Philippe Morency and has published in prestigious journals such as International Journal of Computer Vision, IEEE Transactions on Visualization and Computer Graphics and ACM Transactions on Interactive Intelligent Systems.

In The Last Decade

Fields of papers citing papers by Yale Song

Since Specialization
EngineeringComputer SciencePhysics and AstronomyMathematicsEarth and Planetary SciencesEnergyEnvironmental ScienceMaterials ScienceChemical EngineeringChemistryAgricultural and Biological SciencesVeterinaryDecision SciencesArts and HumanitiesBusiness, Management and AccountingSocial SciencesPsychologyEconomics, Econometrics and FinanceHealth ProfessionsDentistryMedicineBiochemistry, Genetics and Molecular BiologyNeuroscienceNursingImmunology and MicrobiologyPharmacology, Toxicology and Pharmaceutics

This network shows the specialization of papers citing the papers produced by Yale Song. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Yale Song may publish in the future.

Countries citing papers authored by Yale Song

Since Specialization
Citations

This map shows the geographic impact of Yale Song's research. 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 Yale Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yale Song more than expected).

Rankless by CCL
2025