Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Changedetection.net: A new change detection benchmark dataset
2012578 citationsPierre‐Marc Jodoin, Fatih Porikli et al.ANU Open Research (Australian National University)profile →
Big Social Data Analytics in Journalism and Mass Communication
2016158 citationsЛэй Гуо, Weicong Ding et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Prakash Ishwar
Since
Specialization
Citations
This map shows the geographic impact of Prakash Ishwar'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 Prakash Ishwar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prakash Ishwar more than expected).
This network shows the impact of papers produced by Prakash Ishwar. 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 Prakash Ishwar. The network helps show where Prakash Ishwar may publish in the future.
Co-authorship network of co-authors of Prakash Ishwar
This figure shows the co-authorship network connecting the top 25 collaborators of Prakash Ishwar.
A scholar is included among the top collaborators of Prakash Ishwar based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Prakash Ishwar. Prakash Ishwar is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Konrad, Janusz, et al.. (2019). A fully-convolutional neural network for background subtraction of unseen videos. OpenBU (Boston University).2 indexed citations
8.
Ding, Weicong, Prakash Ishwar, & Venkatesh Saligrama. (2015). A Topic Modeling Approach to Ranking. International Conference on Artificial Intelligence and Statistics. 214–222.4 indexed citations
Jodoin, Pierre‐Marc, et al.. (2012). Changedetection.net: A new change detection benchmark dataset. ANU Open Research (Australian National University). 1–8.578 indexed citations breakdown →
13.
Wang, Ye, Nan Ma, Manqi Zhao, Prakash Ishwar, & Venkatesh Saligrama. (2007). On Universal Distributed Estimation of Noisy Fields with One-bit Sensors. arXiv (Cornell University).3 indexed citations
14.
Ishwar, Prakash. (1994). Biodiversity Conservation in the Thar Desert. Indian Forester. 120(10). 873–879.13 indexed citations
15.
Advani, Ranjana H., et al.. (1988). Reduction in rodent populations through intermittent control operations in the cropping ecosystem of the Indian desert. Insecta mundi. 13(13).1 indexed citations
16.
Ishwar, Prakash, et al.. (1984). EFFICACY OF THREE ANTICOAGULANT RODENTICIDES FOR THE CONTROL OF POISON-SHY Rattus rattus. eScholarship (California Digital Library). 11(11).1 indexed citations
17.
Ishwar, Prakash, et al.. (1984). Evaluation of Brodifacoum for the Control of Rattus Meltada And Golunda Ellioti. Indian journal of plant protection. 12(1). 19–23.2 indexed citations
18.
Ishwar, Prakash, et al.. (1980). The metad: a serious rodent pest of Indian agriculture.. Indian Farming. 29(10). 21–23.2 indexed citations
19.
Ishwar, Prakash, et al.. (1967). Intake of seeds of grasses, shrubs and tree species by three species of gerbils in Rajasthan desert.. Indian Forester. 93(12). 801–805.3 indexed citations
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.