Parvez Ahammad

1.0k total citations
28 papers, 639 citations indexed

About

Parvez Ahammad is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Aerospace Engineering. According to data from OpenAlex, Parvez Ahammad has authored 28 papers receiving a total of 639 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 5 papers in Computer Networks and Communications and 5 papers in Aerospace Engineering. Recurrent topics in Parvez Ahammad's work include Advanced Image and Video Retrieval Techniques (5 papers), Robotics and Sensor-Based Localization (5 papers) and Image and Video Quality Assessment (4 papers). Parvez Ahammad is often cited by papers focused on Advanced Image and Video Retrieval Techniques (5 papers), Robotics and Sensor-Based Localization (5 papers) and Image and Video Quality Assessment (4 papers). Parvez Ahammad collaborates with scholars based in United States, Singapore and Hungary. Parvez Ahammad's co-authors include Chuohao Yeo, Kannan Ramchandran, S. Shankar Sastry, Edgar Lobatón, Eugene W. Myers, Songhwai Oh, Phoebus Chen, Simon Wang, Shankar Sastry and Posu Yan and has published in prestigious journals such as SHILAP Revista de lepidopterología, BMC Bioinformatics and International Journal of Computer Vision.

In The Last Decade

Parvez Ahammad

28 papers receiving 609 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Parvez Ahammad United States 13 299 135 134 90 80 28 639
S. Waydo United States 12 175 0.6× 53 0.4× 118 0.9× 27 0.3× 61 0.8× 16 524
Neil Davey United Kingdom 17 110 0.4× 86 0.6× 47 0.4× 19 0.2× 103 1.3× 81 856
Lijuan Duan China 19 420 1.4× 120 0.9× 148 1.1× 10 0.1× 65 0.8× 95 1.1k
Art Pope United States 6 206 0.7× 28 0.2× 18 0.1× 93 1.0× 30 0.4× 11 415
Daniel Gehrig Switzerland 13 364 1.2× 463 3.4× 84 0.6× 11 0.1× 42 0.5× 22 900
Lu Bai China 16 64 0.2× 553 4.1× 142 1.1× 98 1.1× 47 0.6× 51 977
Mu Zhou China 11 102 0.3× 66 0.5× 45 0.3× 31 0.3× 31 0.4× 48 748
Andrea Soltoggio United Kingdom 15 150 0.5× 98 0.7× 112 0.8× 7 0.1× 41 0.5× 43 694
Vinh‐Thong Ta France 12 271 0.9× 21 0.2× 36 0.3× 18 0.2× 43 0.5× 28 606
Leonard Uhr United States 15 295 1.0× 80 0.6× 106 0.8× 20 0.2× 26 0.3× 84 920

Countries citing papers authored by Parvez Ahammad

Since Specialization
Citations

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

Fields of papers citing papers by Parvez Ahammad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Parvez Ahammad

This figure shows the co-authorship network connecting the top 25 collaborators of Parvez Ahammad. A scholar is included among the top collaborators of Parvez Ahammad 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 Parvez Ahammad. Parvez Ahammad 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
1.
Hosseini, Reza, et al.. (2022). Greykite: Deploying Flexible Forecasting at Scale at LinkedIn. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 3007–3017. 4 indexed citations
2.
Liu, Yuelu, et al.. (2019). Machine Learning Models Identify Multimodal Measurements Highly Predictive of Transdiagnostic Symptom Severity for Mood, Anhedonia, and Anxiety. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 5(1). 56–67. 30 indexed citations
3.
Liu, Yuelu, Roee Admon, Emily L. Belleau, et al.. (2019). Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 5(2). 163–172. 19 indexed citations
4.
González, Humberto, et al.. (2018). MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry. arXiv (Cornell University). 19–31. 1 indexed citations
5.
Dey, Prasenjit, et al.. (2017). Perceived Performance of Top Retail Webpages In the Wild. ACM SIGCOMM Computer Communication Review. 47(5). 42–47. 7 indexed citations
6.
Gómez-Marín, Àlex, Vani G. Rajendran, Gus K. Lott, et al.. (2015). Dynamical feature extraction at the sensory periphery guides chemotaxis. eLife. 4. 73 indexed citations
7.
Navlakha, Saket, Parvez Ahammad, & Eugene W. Myers. (2013). Unsupervised segmentation of noisy electron microscopy images using salient watersheds and region merging. BMC Bioinformatics. 14(1). 294–294. 10 indexed citations
8.
Chen, Phoebus, Kirak Hong, S. Shankar Sastry, et al.. (2013). A low-bandwidth camera sensor platform with applications in smart camera networks. ACM Transactions on Sensor Networks. 9(2). 1–23. 23 indexed citations
9.
Zhao, Ting, Jun Xie, Fernando Amat, et al.. (2011). Automated Reconstruction of Neuronal Morphology Based on Local Geometrical and Global Structural Models. Neuroinformatics. 9(2-3). 247–261. 89 indexed citations
10.
Lobatón, Edgar, Parvez Ahammad, & S. Shankar Sastry. (2009). Algebraic approach to recovering topological information in distributed camera networks. Information Processing in Sensor Networks. 193–204. 12 indexed citations
11.
Yeo, Chuohao, Parvez Ahammad, & Kannan Ramchandran. (2008). Rate-efficient visual correspondences using random projections. 217–220. 60 indexed citations
12.
Sastry, S. Shankar & Parvez Ahammad. (2008). Learning data driven representations from large collections of multidimensional patterns with minimal supervision. 1 indexed citations
13.
Yeo, Chuohao, Parvez Ahammad, Kannan Ramchandran, & S. Shankar Sastry. (2008). High-Speed Action Recognition and Localization in Compressed Domain Videos. IEEE Transactions on Circuits and Systems for Video Technology. 18(8). 1006–1015. 42 indexed citations
14.
Ahammad, Parvez, Chuohao Yeo, Kannan Ramchandran, & S. Shankar Sastry. (2007). Unsupervised Discovery of Action Hierarchies in Large Collections of Activity Videos. 410–413. 2 indexed citations
15.
Yeo, Chuohao, Parvez Ahammad, & Kannan Ramchandran. (2007). A rate-efficient approach for establishing visual correspondences via distributed source coding. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6822. 68221R–68221R. 4 indexed citations
16.
Yeo, Chuohao, Parvez Ahammad, Kannan Ramchandran, & S. Shankar Sastry. (2006). Compressed Domain Real-time Action Recognition. 33–36. 16 indexed citations
17.
Ahammad, Parvez, Cyrus L. Harmon, Ann S. Hammonds, Shankar Sastry, & Gerald M. Rubin. (2005). Joint Nonparametric Alignment for Analyzing Spatial Gene Expression Patterns in Drosophila Imaginal Discs. 2. 755–760. 4 indexed citations
18.
Learned-Miller, Erik & Parvez Ahammad. (2004). Joint MRI Bias Removal Using Entropy Minimization Across Images. ScholarWorks@UMassAmherst (University of Massachusetts Amherst). 17. 761–768. 16 indexed citations
19.
Ahammad, Parvez & Amar Mukherjee. (2002). Modified Shape from Shading Approach to SEM based Photoresist CD Metrology. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4889. 365–365. 2 indexed citations
20.
Ahammad, Parvez, Christopher R. Williams, Takis Kasparis, et al.. (2002). <title>Vertical air motion estimates from the disdrometer flux conservation model and related experimental observations</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4729. 384–393. 2 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.

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