Shagan Sah

545 total citations
23 papers, 336 citations indexed

About

Shagan Sah is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction. According to data from OpenAlex, Shagan Sah has authored 23 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 3 papers in Human-Computer Interaction. Recurrent topics in Shagan Sah's work include Human Pose and Action Recognition (10 papers), Multimodal Machine Learning Applications (9 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Shagan Sah is often cited by papers focused on Human Pose and Action Recognition (10 papers), Multimodal Machine Learning Applications (9 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Shagan Sah collaborates with scholars based in United States and China. Shagan Sah's co-authors include Raymond Ptucha, Felipe Petroski Such, Chao Zhang, Andrew Michael, Nathan D. Cahill, Subhashini Venugopalan, Emily Prud’hommeaux, Allison Gray, Saloni Jain and Alexander C. Loui and has published in prestigious journals such as IEEE Journal of Selected Topics in Signal Processing, Pattern Analysis and Applications and Journal of Electronic Imaging.

In The Last Decade

Shagan Sah

22 papers receiving 317 citations

Peers

Countries citing papers authored by Shagan Sah

Since Specialization

Citations

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

Fields of papers citing papers by Shagan Sah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shagan Sah

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Deep Learning Methods for Sign Language Translation 2021 ·ACM Transactions on Accessible Computing ·(unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Shagan Sah, Thomastine Sarchet, Raymond Ptucha, Ifeoma Nwogu	29
2	Machine Learning: A Review of Learning Types 2020 ·Preprints.org ·Shagan Sah	45
3	Understanding temporal structure for video captioning 2019 ·Pattern Analysis and Applications ·Shagan Sah, (unknown), (unknown)	10
4	Show, Translate and Tell 2019 ·(unknown), Shagan Sah, Raymond Ptucha	2
5	Large Scale Sign Language Interpretation 2019 ·(unknown), Shagan Sah, (unknown), Chi Zhang, (unknown), (unknown), Raymond Ptucha	16
6	Multimodal Reconstruction Using Vector Representation 2018 ·Shagan Sah, (unknown), (unknown), John F. Hamilton, Andreas Savakis, (unknown)	0
7	Semantic sentence embeddings for paraphrasing and text summarization 2017 ·Chi Zhang, Shagan Sah, (unknown), (unknown), Alexander C. Loui, Carl Salvaggio, Raymond Ptucha	11
8	Temporally Steered Gaussian Attention for Video Understanding 2017 ·Shagan Sah, (unknown), (unknown), Felipe Petroski Such, Raymond Ptucha	2
9	Batch-normalized recurrent highway networks 2017 ·arXiv (Cornell University) ·Chi Zhang, (unknown), Shagan Sah, Raymond Ptucha, Alexander C. Loui, Carl Salvaggio	4
10	Multistream hierarchical boundary network for video captioning 2017 ·(unknown), Shagan Sah, Raymond Ptucha	3
11	Robust Spatial Filtering With Graph Convolutional Neural Networks 2017 ·IEEE Journal of Selected Topics in Signal Processing ·Felipe Petroski Such, Shagan Sah, (unknown), (unknown), Chao Zhang, Andrew Michael, Nathan D. Cahill, Raymond Ptucha	95
12	Video redaction: a survey and comparison of enabling technologies 2017 ·Journal of Electronic Imaging ·Shagan Sah, (unknown), Raymond Ptucha, (unknown), Robert P. Loce	10
13	Semantic Text Summarization of Long Videos 2017 ·Shagan Sah, (unknown), Allison Gray, Subhashini Venugopalan, Emily Prud’hommeaux, Raymond Ptucha	37
14	Towards 3D convolutional neural networks with meshes 2017 ·(unknown), Felipe Petroski Such, Shagan Sah, Raymond Ptucha	9
15	Adaptive hierarchical classification networks 2016 ·(unknown), (unknown), (unknown), Shagan Sah, Raymond Ptucha	3
16	Hierarchical Decomposition of Large Deep Networks 2016 ·Electronic Imaging ·(unknown), Shagan Sah, (unknown), Raymond Ptucha	4
17	Image description through fusion based recurrent multi-modal learning 2016 ·(unknown), Shagan Sah, (unknown), Raymond Ptucha	4
18	Automatic scanpath generation with deep recurrent neural networks 2016 ·(unknown), Srinivas Sridharan, Shagan Sah, Raymond Ptucha, (unknown), Reynold Bailey	3
19	A multi-temporal fusion-based approach for land cover mapping in support of nuclear incident response 2013 ·RIT Scholar Works (Rochester Institute of Technology) ·Shagan Sah	1
20	A multi-temporal analysis approach for land cover mapping in support of nuclear incident response 2012 ·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·Shagan Sah, J. A. N. van Aardt, (unknown), David W. Messinger	1

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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