Anwaar Ulhaq

50 papers receiving 1.1k citations

Hit Papers

Depression detection from social network data using machi...2018202620202023201850100150200250

Peers

Anwaar Ulhaq
Comparison fields: 5 of 122
  • Artificial Intelligence 450
  • Radiology, Nuclear Medicine and Imaging 367
  • Social Psychology 217
  • Computer Vision and Pattern Recognition 134
  • Applied Psychology 127
Replace Stephan K. Chalup with:
Stephan K. Chalup Australia
Robert Dürichen Germany
Lu Bai China
Carlos Eduardo Thomaz Brazil
Ognjen Arandjelović United Kingdom
Elena Hernández-Pereira Spain
Ting Yang China
Mohammad Khubeb Siddiqui Australia
Giovanni Luca Masala Italy
Deepa Gupta India
Anwaar Ulhaq relative to Stephan K. Chalup Australia Stephan K. Chalup's profile →
Citations per field
00.5×6.9×
Stephan K. Chalup · 1×
Citations per year

Countries citing papers authored by Anwaar Ulhaq

Since Specialization
Citations

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

Fields of papers citing papers by Anwaar Ulhaq

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anwaar Ulhaq

This figure shows the co-authorship network connecting the top 25 collaborators of Anwaar Ulhaq. A scholar is included among the top collaborators of Anwaar Ulhaq 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 Anwaar Ulhaq. Anwaar Ulhaq is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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The role of information fusion in transfer learning of obscure human activities during night
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Depression detection from social network data using machine learning techniquesbreakdown →
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A Novel Image Fusion Algorithm Based on Kernel-PCA, DWT and Structural Similarity
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About Anwaar Ulhaq

Anwaar Ulhaq is a scholar working on Health Informatics, Media Technology and Computer Vision and Pattern Recognition, having authored 57 papers that have together received 1.1k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (8 papers), Remote Sensing and LiDAR Applications (6 papers) and Remote Sensing and Land Use (5 papers). The work is most often cited by research in Health Informatics (68 citations), Applied Psychology (127 citations) and Radiology, Nuclear Medicine and Imaging (367 citations). Anwaar Ulhaq has collaborated with scholars based in Australia, Bangladesh and Pakistan. Frequent co-authors include Manoranjan Paul, Subrata Chakraborty, Abu Raihan Mostofa Kamal, Douglas Pinto Sampaio Gomes, Michael J. Horry, Nagesh Shukla, Biswajeet Pradhan, Manas Saha, Muhammad Ashad Kabir and Md. Rafiqul Islam. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Image Processing.

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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