Tamer Shanableh

2.0k total citations
83 papers, 1.4k citations indexed

About

Tamer Shanableh is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Human-Computer Interaction. According to data from OpenAlex, Tamer Shanableh has authored 83 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Computer Vision and Pattern Recognition, 37 papers in Signal Processing and 22 papers in Human-Computer Interaction. Recurrent topics in Tamer Shanableh's work include Video Coding and Compression Technologies (33 papers), Hand Gesture Recognition Systems (21 papers) and Human Pose and Action Recognition (18 papers). Tamer Shanableh is often cited by papers focused on Video Coding and Compression Technologies (33 papers), Hand Gesture Recognition Systems (21 papers) and Human Pose and Action Recognition (18 papers). Tamer Shanableh collaborates with scholars based in United Arab Emirates, United Kingdom and United States. Tamer Shanableh's co-authors include Khaled Assaleh, M. Ghanbari, M. Al‐Rousan, Eduardo Peixoto, Assim Sagahyroon, Ebroul Izquierdo, A. R. Al-Ali, Omar Hamdan, M. Amin Farajian and Alexandre Zaghetto and has published in prestigious journals such as IEEE Access, Neurocomputing and Journal of the Franklin Institute.

In The Last Decade

Tamer Shanableh

80 papers receiving 1.3k citations

Peers

Tamer Shanableh
Chung‐Lin Huang Taiwan
Rabul Hussain Laskar India
Jehan Wickramasuriya United States
Venu Vasudevan United States
Jiayang Liu China
Jonathan Alon United States
Kourosh Kiani Iran
David Demirdjian United States
Fernando Jaureguizar Spain
Muneer Al-Hammadi Saudi Arabia
Chung‐Lin Huang Taiwan
Tamer Shanableh
Citations per year, relative to Tamer Shanableh Tamer Shanableh (= 1×) peers Chung‐Lin Huang

Countries citing papers authored by Tamer Shanableh

Since Specialization
Citations

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

Fields of papers citing papers by Tamer Shanableh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tamer Shanableh

This figure shows the co-authorship network connecting the top 25 collaborators of Tamer Shanableh. A scholar is included among the top collaborators of Tamer Shanableh 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 Tamer Shanableh. Tamer Shanableh 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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Shanableh, Tamer, et al.. (2024). Hand-Crafted Features With a Simple Deep Learning Architecture for Sensor-Based Human Activity Recognition. IEEE Sensors Journal. 24(17). 28300–28313. 3 indexed citations
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Shanableh, Tamer, et al.. (2024). LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications. Algorithms. 17(7). 280–280. 3 indexed citations
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Shanableh, Tamer, et al.. (2023). Video-Based Recognition of Human Activity Using Novel Feature Extraction Techniques. Applied Sciences. 13(11). 6856–6856. 1 indexed citations
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Shanableh, Tamer, et al.. (2023). Static Video Summarization Using Video Coding Features with Frame-Level Temporal Subsampling and Deep Learning. Applied Sciences. 13(10). 6065–6065. 8 indexed citations
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Shanableh, Tamer, et al.. (2022). CNN and HEVC Video Coding Features for Static Video Summarization. IEEE Access. 10. 72080–72091. 15 indexed citations
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Shanableh, Tamer, et al.. (2020). Predicting split decisions in MPEG-2 to HEVC video transcoding. SN Applied Sciences. 2(6). 7 indexed citations
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Shanableh, Tamer. (2020). Recursive Quad-Tree Block Partitioning for Data Embedding in Images. SN Computer Science. 1(6). 3 indexed citations
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Shanableh, Tamer, et al.. (2019). IoT Based Smart Bus Stops. 6–9. 4 indexed citations
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Shanableh, Tamer, et al.. (2017). Novel Classification System for Classifying Cognitive Workload Levels Under Vague Visual Stimulation. IEEE Sensors Journal. 17(21). 7019–7028. 22 indexed citations
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Assaleh, Khaled, et al.. (2016). User-Dependent Sign Language Recognition Using Motion Detection. 852–856. 20 indexed citations
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Sagahyroon, Assim, et al.. (2015). FPGA-Based Parallel Hardware Architecture for Real-Time Image Classification. IEEE Transactions on Computational Imaging. 1(1). 56–70. 34 indexed citations
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Shanableh, Tamer, et al.. (2013). MPEG-2 to HEVC Video Transcoding With Content-Based Modeling. IEEE Transactions on Circuits and Systems for Video Technology. 23(7). 1191–1196. 42 indexed citations
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Shanableh, Tamer. (2011). Data Hiding in MPEG Video Files Using Multivariate Regression and Flexible Macroblock Ordering. IEEE Transactions on Information Forensics and Security. 7(2). 455–464. 65 indexed citations
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Assaleh, Khaled, et al.. (2010). Enhanced user-dependent recognition of Arabic Sign language via disparity images. 1–4. 2 indexed citations
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Assaleh, Khaled, et al.. (2010). Continuous Arabic Sign Language Recognition in User Dependent Mode. DSpace at AUS (American University of Sharjah). 2(1). 19–27. 40 indexed citations
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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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