Saad Bin Abul Kashem

3.4k total citations · 3 hit papers
53 papers, 1.9k citations indexed

About

Saad Bin Abul Kashem is a scholar working on Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment and Control and Systems Engineering. According to data from OpenAlex, Saad Bin Abul Kashem has authored 53 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Electrical and Electronic Engineering, 9 papers in Renewable Energy, Sustainability and the Environment and 8 papers in Control and Systems Engineering. Recurrent topics in Saad Bin Abul Kashem's work include Photovoltaic System Optimization Techniques (8 papers), COVID-19 diagnosis using AI (6 papers) and Solar Radiation and Photovoltaics (5 papers). Saad Bin Abul Kashem is often cited by papers focused on Photovoltaic System Optimization Techniques (8 papers), COVID-19 diagnosis using AI (6 papers) and Solar Radiation and Photovoltaics (5 papers). Saad Bin Abul Kashem collaborates with scholars based in Qatar, Malaysia and Bangladesh. Saad Bin Abul Kashem's co-authors include Muhammad E. H. Chowdhury, Amith Khandakar, Tawsifur Rahman, Mohammad Tariqul Islam, Zaid Bin Mahbub, Muhammad Abdul Kadir, Khandaker Reajul Islam, Susu M. Zughaier, Muhammad Salman Khan and Somaya Al-Máadeed and has published in prestigious journals such as Scientific Reports, IEEE Access and Waste Management.

In The Last Decade

Saad Bin Abul Kashem

48 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images

2021 672 citations Tawsifur Rahman, Amith Khandakar et al. Computers in Biology and Medicine profile →
Transfer Learning with Deep Convolutional Neural Network (CNN) for Pneumonia Detection Using Chest X-ray

2020 394 citations Tawsifur Rahman, Muhammad E. H. Chowdhury et al. profile →
Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization

2020 375 citations Tawsifur Rahman, Amith Khandakar et al. IEEE Access profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Saad Bin Abul Kashem Qatar	16	1.2k	756	319	271	124	53	1.9k
Yazan Qiblawey Qatar	11	762 0.6×	519 0.7×	194 0.6×	146 0.5×	140 1.1×	21	1.1k
Nour Eldeen M. Khalifa Egypt	16	1.0k 0.8×	699 0.9×	817 2.6×	203 0.7×	84 0.7×	33	2.0k
Narendra D. Londhe India	25	492 0.4×	438 0.6×	256 0.8×	392 1.4×	151 1.2×	125	1.9k
Mohamed Loey Egypt	14	1.1k 0.9×	793 1.0×	953 3.0×	238 0.9×	87 0.7×	24	2.2k
Burhan Ergen Türkiye	25	1.1k 0.9×	1.2k 1.5×	878 2.8×	222 0.8×	151 1.2×	90	2.6k
Radim Bürget Czechia	22	557 0.5×	443 0.6×	554 1.7×	171 0.6×	224 1.8×	139	1.8k
Hazrat Ali Pakistan	19	332 0.3×	519 0.7×	430 1.3×	76 0.3×	163 1.3×	119	1.5k
Mesut Toğaçar Türkiye	22	1.2k 1.0×	1.2k 1.6×	761 2.4×	188 0.7×	138 1.1×	57	2.3k
Marios Anthimopoulos Switzerland	14	807 0.7×	608 0.8×	474 1.5×	395 1.5×	363 2.9×	20	2.0k
Tao Zhou China	14	344 0.3×	365 0.5×	274 0.9×	97 0.4×	105 0.8×	132	1.1k

Countries citing papers authored by Saad Bin Abul Kashem

Since Specialization

Citations

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

Fields of papers citing papers by Saad Bin Abul Kashem

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Saad Bin Abul Kashem. 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 Saad Bin Abul Kashem. The network helps show where Saad Bin Abul Kashem may publish in the future.

Co-authorship network of co-authors of Saad Bin Abul Kashem

This figure shows the co-authorship network connecting the top 25 collaborators of Saad Bin Abul Kashem. A scholar is included among the top collaborators of Saad Bin Abul Kashem 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 Saad Bin Abul Kashem. Saad Bin Abul Kashem 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

Khandakar, Amith, et al.. (2025). Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection. IEEE Access. 13. 42322–42335. 1 indexed citations

Ali, Mohamed Sultan Mohamed, et al.. (2025). A hybrid 3D CNN-LSTM model with soft spatial attention mechanism for accurate hyperspectral image classification. Remote Sensing Applications Society and Environment. 40. 101779–101779.

Khandakar, Amith, et al.. (2024). Enhancing waste sorting and recycling efficiency: robust deep learning-based approach for classification and detection. Neural Computing and Applications. 37(6). 4567–4583. 10 indexed citations

Kashem, Saad Bin Abul, et al.. (2024). ECCDN-Net: A deep learning-based technique for efficient organic and recyclable waste classification. Waste Management. 193. 363–375. 6 indexed citations

Kashem, Saad Bin Abul, et al.. (2024). A Reliable and Robust Deep Learning Model for Effective Recyclable Waste Classification. IEEE Access. 12. 13809–13821. 27 indexed citations

Kashem, Saad Bin Abul, et al.. (2023). Life Cycle Assessment of Biofuel Production from Household Waste and the Sustainability of the Processes: A Comprehensive Review. SSRN Electronic Journal.

Kashem, Saad Bin Abul, et al.. (2023). GCDN-Net: Garbage classifier deep neural network for recyclable urban waste management. Waste Management. 174. 439–450. 25 indexed citations

Tabassum, Mujahid, Sundresan Perumal, Saad Bin Abul Kashem, et al.. (2022). Enhance data availability and network consistency using artificial neural network for IoT. Multimedia Tools and Applications. 83(1). 3111–3131. 6 indexed citations

Rahman, Tawsifur, Amith Khandakar, Md. Ahasan Atick Faisal, et al.. (2022). QCovSML: A reliable COVID-19 detection system using CBC biomarkers by a stacking machine learning model. Computers in Biology and Medicine. 143. 105284–105284. 31 indexed citations

10.

Kashem, Saad Bin Abul, et al.. (2022). A Review and Analysis of the Effects of Colors of Light On the Performance of Solar Photovoltaic Panels. International Journal of Integrated Engineering. 14(4).

11.

Hossain, Amran, Mohammad Tariqul Islam, Kok Beng Gan, et al.. (2022). Microwave brain imaging system to detect brain tumor using metamaterial loaded stacked antenna array. Scientific Reports. 12(1). 16478–16478. 33 indexed citations

12.

Ahmed, Jubaer, et al.. (2021). Basic Home Automation Using Smart Sockets with Power Management. International Journal of Integrated Engineering. 13(2).

13.

Rahman, Tawsifur, Amith Khandakar, Yazan Qiblawey, et al.. (2021). Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images. Computers in Biology and Medicine. 132. 104319–104319. 672 indexed citations breakdown →

14.

Rahman, Tawsifur, Amith Khandakar, Md Enamul Hoque, et al.. (2021). Development and Validation of an Early Scoring System for Prediction of Disease Severity in COVID-19 Using Complete Blood Count Parameters. IEEE Access. 9. 120422–120441. 23 indexed citations

15.

Rahman, Tawsifur, Amith Khandakar, Muhammad Abdul Kadir, et al.. (2020). Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization. IEEE Access. 8. 191586–191601. 375 indexed citations breakdown →

16.

Kashem, Saad Bin Abul, et al.. (2020). A Comprehensive Study and Analysis of Kinetic Energy Floor. Acta Energetica Power Engineering Quarterly. 6–13. 2 indexed citations

17.

Kashem, Saad Bin Abul, et al.. (2020). A Preliminary Study and Analysis of Tidal Stream Generators. Acta Energetica Power Engineering Quarterly. 6–22. 4 indexed citations

18.

Kashem, Saad Bin Abul, et al.. (2019). Design and Implementation of a Quadruped Amphibious Robot Using Duck Feet. Robotics. 8(3). 77–77. 12 indexed citations

19.

Kashem, Saad Bin Abul, et al.. (2017). A novel design of an amphibious robot having webbed feet as duck. Swinburne Research Bank (Swinburne University of Technology). 17–21. 2 indexed citations

20.

Kashem, Saad Bin Abul, et al.. (2016). Comparison of different energy saving lights using solar panel. Frontiers in Energy. 10(4). 466–472. 4 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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