Pranamesh Chakraborty

774 citations
24 papers · 460 indexed · h-index 11

Pranamesh Chakraborty

23 papers receiving 442 citations

Peers

Pranamesh Chakraborty
Comparison fields: 5 of 74
  • Building and Construction 224
  • Transportation 100
  • Automotive Engineering 92
  • Computer Vision and Pattern Recognition 144
  • Safety, Risk, Reliability and Quality 57
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Citations per year

Countries citing papers authored by Pranamesh Chakraborty

Since Specialization
Citations

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

Fields of papers citing papers by Pranamesh Chakraborty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pranamesh Chakraborty. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pranamesh Chakraborty. The network helps show where Pranamesh Chakraborty may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Pranamesh Chakraborty, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pranamesh Chakraborty Line = papers co-authored together Pranamesh Chakraborty links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202412
2 20234
3 20231
4 20225
5 20211
6 202129
7 20214
8 202074
9
The 2019 AI City Challenge.
201915
10 20197
11 201932
12 201913
13
Comparison of Machine Learning Algorithms to Determine Traffic Congestion from Camera Images
20182
14 201856
15 201887
16 201854
17 201835
18
Outlier Mining Based Traffic Incident Detection Using Big Data Analytics
20177
19
Trend Filtering in Network Time Series with Applications to Traffic Incident Detection
20172
20 20171

About Pranamesh Chakraborty

Pranamesh Chakraborty is a scholar working on Building and Construction, Transportation and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 460 indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (16 papers), Anomaly Detection Techniques and Applications (7 papers), Video Surveillance and Tracking Methods (6 papers), Traffic control and management (4 papers), Transportation Planning and Optimization (3 papers), Autonomous Vehicle Technology and Safety (3 papers), Image and Signal Denoising Methods (2 papers) and Gaze Tracking and Assistive Technology (2 papers). The work is most often cited by research in Building and Construction (224 citations), Transportation (100 citations) and Automotive Engineering (92 citations). Pranamesh Chakraborty has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Anuj Sharma, Chinmay Hegde, Soumik Sarkar, Yaw Adu‐Gyamfi, Arya Haghighat, Mingyi Hong, Stephen B. Gilbert, Anuj Sharma, David C. Anastasiu and Milind Naphade. Their work appears in journals such as Transportation Planning and Technology, Engineering Applications of Artificial Intelligence, Traffic Injury Prevention, Accident Analysis & Prevention and Transportation Research Part C Emerging Technologies.

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.

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