M. Saeed Darweesh

763 total citations
68 papers, 405 citations indexed

About

M. Saeed Darweesh is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, M. Saeed Darweesh has authored 68 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 23 papers in Electrical and Electronic Engineering and 14 papers in Artificial Intelligence. Recurrent topics in M. Saeed Darweesh's work include Autonomous Vehicle Technology and Safety (12 papers), Energy Harvesting in Wireless Networks (6 papers) and Face recognition and analysis (6 papers). M. Saeed Darweesh is often cited by papers focused on Autonomous Vehicle Technology and Safety (12 papers), Energy Harvesting in Wireless Networks (6 papers) and Face recognition and analysis (6 papers). M. Saeed Darweesh collaborates with scholars based in Egypt, United Kingdom and United Arab Emirates. M. Saeed Darweesh's co-authors include Ahmed Soltan, Hassan Mostafa, Tawfik Ismail, Mohamed Adel, Mustafa Elattar, Ahmed Kotb, Haitham Mahmoud, Hossam E. Abd El Munim, Maged Ghoneima and Khaled Elsayed and has published in prestigious journals such as Scientific Reports, IEEE Access and Alexandria Engineering Journal.

In The Last Decade

M. Saeed Darweesh

57 papers receiving 386 citations

Peers

M. Saeed Darweesh
M. Saeed Darweesh
Citations per year, relative to M. Saeed Darweesh M. Saeed Darweesh (= 1×) peers Trung‐Kien Dao

Countries citing papers authored by M. Saeed Darweesh

Since Specialization
Citations

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

Fields of papers citing papers by M. Saeed Darweesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Saeed Darweesh. 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 M. Saeed Darweesh. The network helps show where M. Saeed Darweesh may publish in the future.

Co-authorship network of co-authors of M. Saeed Darweesh

This figure shows the co-authorship network connecting the top 25 collaborators of M. Saeed Darweesh. A scholar is included among the top collaborators of M. Saeed Darweesh 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 M. Saeed Darweesh. M. Saeed Darweesh 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.
Darweesh, M. Saeed, et al.. (2024). Federated learning system on autonomous vehicles for lane segmentation. Scientific Reports. 14(1). 25029–25029. 6 indexed citations
2.
Darweesh, M. Saeed, et al.. (2024). Enhancing Network Threat Detection with Random Forest-Based NIDS and Permutation Feature Importance. Journal of Network and Systems Management. 33(1). 8 indexed citations
3.
Darweesh, M. Saeed, et al.. (2024). Early Skin Cancer Detection Based on MobileNet & VGG-16. 384–389. 1 indexed citations
4.
Elattar, Mustafa, et al.. (2023). A novel data augmentation approach for ego-lane detection enhancement. Evolving Systems. 15(3). 1021–1032. 2 indexed citations
5.
Darweesh, M. Saeed, et al.. (2023). Smart Attendance Marking System Based on BLE. 269–275.
8.
Soltan, Ahmed, et al.. (2023). A power-aware task scheduler for energy harvesting-based wearable biomedical systems using snake optimizer. Analog Integrated Circuits and Signal Processing. 115(2). 183–194. 13 indexed citations
9.
Darweesh, M. Saeed, et al.. (2023). A comparative study of predicting the availability of power line communication nodes using machine learning. Scientific Reports. 13(1). 12658–12658. 3 indexed citations
10.
Elattar, Mustafa, et al.. (2023). Joint Sign Language Recognition and Translation Using Keypoint Estimation. 9. 184–189. 1 indexed citations
11.
Mohamed, Ali Wagdy, et al.. (2023). Energy management for wearable medical devices based on gaining–sharing knowledge algorithm. Complex & Intelligent Systems. 9(6). 6797–6811. 6 indexed citations
12.
14.
Medhat, Walaa, et al.. (2022). Sentiment Analysis: Amazon Electronics Reviews Using BERT and Textblob. 6–10. 7 indexed citations
15.
Elattar, Mustafa, et al.. (2021). A Deep Learning-Based Benchmarking Framework for Lane Segmentation in the Complex and Dynamic Road Scenes. IEEE Access. 9. 117565–117580. 15 indexed citations
16.
Ismail, Tawfik, et al.. (2020). Real-Time Collision Warning System Based on Computer Vision Using Mono Camera. 60–64. 11 indexed citations
19.
Mahmoud, Haitham, Tawfik Ismail, & M. Saeed Darweesh. (2020). Optimal Function Split via Joint Optimization of Power Consumption and Bandwidth in V-RAN. BCU Open Access Repository (Birmingham City University). 1–5. 9 indexed citations
20.
Munim, Hossam E. Abd El, et al.. (2018). Real-Time Car Detection-Based Depth Estimation Using Mono Camera. 248–251. 8 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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