Caleb Robinson

32 papers receiving 959 citations

Caleb Robinson's Hit Papers

Machine learning approaches for estimating commercial building energy consumption 2017 · 402 citations
4020+3+6Years since publication100200300400

Peers

Caleb Robinson
Comparison fields: 5 of 109
  • Building and Construction 323
  • Environmental Engineering 244
  • Media Technology 148
  • Transportation 74
  • Speech and Hearing 50
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Zhen Qian China
Teng Zhong China
Jason Brown United States
Teresa Santos Portugal
Xin Ye China
Hugh Forehead Australia
Tianhong Zhao China
Liu Liu China
Mila Koeva Netherlands
Jianzheng Liu China
Caleb Robinson relative to Zhen Qian China Zhen Qian's profile →
Citations per field
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Citations per year

Countries citing papers authored by Caleb Robinson

Since Specialization
Citations

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

Fields of papers citing papers by Caleb Robinson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Caleb Robinson. 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 Caleb Robinson. The network helps show where Caleb Robinson may publish in the future.

Co-authors

The 25 scholars most cited alongside Caleb Robinson, 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 Caleb Robinson Line = papers co-authored together Caleb Robinson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine learning approaches for estimating commercial building energy consumption
Hit paper breakdown →
2017402
2 201872
3 201969
4 202057
5 202148
6 201847
7 202236
8 202232
9 202229
10 202227
11 202417
12 202314
13 202013
14 202513
15 202412
16 202212
17
Label super-resolution networks.
201811
18 202211
19 202110
20 202210

About Caleb Robinson

Caleb Robinson is a scholar working on Media Technology, Global and Planetary Change, Ecology, Artificial Intelligence and Sociology and Political Science, having authored 36 papers that have together received 995 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (9 papers), Remote Sensing in Agriculture (5 papers), Automated Road and Building Extraction (4 papers), Impact of Light on Environment and Health (4 papers), Flood Risk Assessment and Management (3 papers), Disaster Management and Resilience (3 papers), Anomaly Detection Techniques and Applications (3 papers) and Urban Transport and Accessibility (3 papers). The work is most often cited by research in Building and Construction (323 citations), Environmental Engineering (244 citations), Media Technology (148 citations), Transportation (74 citations) and Speech and Hearing (50 citations). Caleb Robinson has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Bistra Dilkina, Marilyn A. Brown, Subhrajit Guhathakurta, Ram M. Pendyala, Wenwen Zhang, Juan Lavista Ferres, Nebojša Jojić, Anthony Ortiz, Juan Moreno‐Cruz and Le Hou. Their work appears in journals such as PLoS ONE, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Geoscience and Remote Sensing Magazine, Scientific Data and Frontiers in Environmental Science.

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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