Bin Bi

About

Bin Bi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Pollution. According to data from OpenAlex, Bin Bi has authored 24 papers receiving a total of 755 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 3 papers in Pollution. Recurrent topics in Bin Bi’s work include Topic Modeling (9 papers), Natural Language Processing Techniques (9 papers) and Multimodal Machine Learning Applications (9 papers). Bin Bi is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (9 papers) and Multimodal Machine Learning Applications (9 papers). Bin Bi collaborates with scholars based in China, United States and Cayman Islands. Bin Bi's co-authors include Songfang Huang, Luo Si, Shaoyong Lu, Ming Yan and Fei Huang and has published in prestigious journals such as Environmental Pollution, Chemosphere and RSC Advances.

In The Last Decade

Fields of papers citing papers by Bin Bi

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 Bin Bi. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Bin Bi may publish in the future.

Countries citing papers authored by Bin Bi

Since Specialization

Citations

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

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