Sheeraz Arif

532 total citations
12 papers, 328 citations indexed

About

Sheeraz Arif is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Sheeraz Arif has authored 12 papers receiving a total of 328 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 4 papers in Biomedical Engineering. Recurrent topics in Sheeraz Arif's work include Human Pose and Action Recognition (5 papers), Video Surveillance and Tracking Methods (4 papers) and Anomaly Detection Techniques and Applications (3 papers). Sheeraz Arif is often cited by papers focused on Human Pose and Action Recognition (5 papers), Video Surveillance and Tracking Methods (4 papers) and Anomaly Detection Techniques and Applications (3 papers). Sheeraz Arif collaborates with scholars based in China, United Kingdom and India. Sheeraz Arif's co-authors include Greg Slabaugh, Karen Knapp, Fida Hussain, Yue Shen, Hui Liu, Muhammad Abubakar, Jing Wang, Zesong Fei, Muhammad Asad and Philip J. Corr and has published in prestigious journals such as Computer Methods and Programs in Biomedicine, Electric Power Systems Research and Signal Processing Image Communication.

In The Last Decade

Sheeraz Arif

12 papers receiving 316 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sheeraz Arif China	7	115	92	66	64	48	12	328
Xikai Tu China	11	58 0.5×	280 3.0×	112 1.7×	30 0.5×	5 0.1×	36	474
Zhen Deng China	13	27 0.2×	204 2.2×	156 2.4×	94 1.5×	57 1.2×	48	539
Zhuoqi Cheng Denmark	12	132 1.1×	179 1.9×	50 0.8×	33 0.5×	72 1.5×	39	325
Shahzad Ahmed South Korea	11	105 0.9×	227 2.5×	19 0.3×	81 1.3×	38 0.8×	25	494
Hao Gong China	11	31 0.3×	37 0.4×	31 0.5×	65 1.0×	23 0.5×	34	376
Farzad Shahabi United States	7	82 0.7×	110 1.2×	32 0.5×	197 3.1×	10 0.2×	18	410
Mokhtar Attari Algeria	10	103 0.9×	176 1.9×	28 0.4×	50 0.8×	32 0.7×	36	313
Erkan Kaplanoğlu Türkiye	9	16 0.1×	138 1.5×	57 0.9×	38 0.6×	7 0.1×	49	372
Iván Salgado Mexico	15	110 1.0×	121 1.3×	371 5.6×	22 0.3×	7 0.1×	55	550
Branesh M. Pillai Thailand	8	33 0.3×	73 0.8×	69 1.0×	33 0.5×	43 0.9×	42	248

Countries citing papers authored by Sheeraz Arif

Since Specialization

Citations

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

Fields of papers citing papers by Sheeraz Arif

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheeraz Arif

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

All Works

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12 of 12 papers shown

Arif, Sheeraz, et al.. (2023). An Efficient Loan Approval Status Prediction Using Machine Learning. 1–6. 4 indexed citations

Arif, Sheeraz, et al.. (2021). Bidirectional LSTM with saliency-aware 3D-CNN features for human action recognition. Journal of Engineering Research. 9(3). 115–133. 9 indexed citations

Yang, Shu, et al.. (2021). SAL‐Net: Self‐Supervised Attribute Learning for Object Recognition and Segmentation. Wireless Communications and Mobile Computing. 2021(1). 4 indexed citations

Arif, Sheeraz, Jing Wang, Fida Hussain, & Zesong Fei. (2019). Trajectory-Based 3D Convolutional Descriptors for Human Action Recognition.. Journal of information science and engineering. 35. 851–870. 3 indexed citations

Arif, Sheeraz, et al.. (2019). 3D-CNN-Based Fused Feature Maps with LSTM Applied to Action Recognition. Future Internet. 11(2). 42–42. 46 indexed citations

Arif, Sheeraz, Jing Wang, Zesong Fei, & Fida Hussain. (2019). Video Representation via Fusion of Static and Motion Features Applied to Human Activity Recognition. KSII Transactions on Internet and Information Systems. 13(7). 3 indexed citations

Arif, Sheeraz, Karen Knapp, & Greg Slabaugh. (2018). Fully automatic cervical vertebrae segmentation framework for X-ray images. Computer Methods and Programs in Biomedicine. 157. 95–111. 91 indexed citations

Arif, Sheeraz, et al.. (2018). Video representation by dense trajectories motion map applied to human activity recognition. International Journal of Computers and Applications. 42(5). 474–484. 4 indexed citations

Liu, Hui, et al.. (2018). Complex power quality disturbances classification via curvelet transform and deep learning. Electric Power Systems Research. 163. 1–9. 108 indexed citations

10.

Gao, Fei, et al.. (2018). Interference Management in Femtocells by the Adaptive Network Sensing Power Control Technique. Future Internet. 10(3). 25–25. 6 indexed citations

11.

Riaz, Atif, Muhammad Asad, Sheeraz Arif, et al.. (2018). Deep fMRI: AN end-to-end deep network for classification of fMRI data. City Research Online (City University London). 41 indexed citations

12.

Arif, Sheeraz, et al.. (2017). Patch-based corner detection for cervical vertebrae in X-ray images. Signal Processing Image Communication. 59. 27–36. 9 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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