Mohamed Abdou | Mathematics | Excellence Award (Any Scientific field)

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Prof. Dr. Mohamed Abdou | Mathematics | Excellence Award (Any Scientific field)

Head Mathematics Department, Alexandria University – Faculty of Education, Egypt

Dr. Mohamed Abdou is a distinguished researcher and academic specializing in mathematical modeling, integral equations, and computational mathematics. With a robust track record in publishing high-impact articles, Dr. Abdou is a pivotal figure in advancing numerical methods for solving complex mathematical problems. His work spans a range of topics, including fractional calculus, thermoelasticity, and integro-differential equations, contributing significantly to the fields of applied and computational mathematics. 📚🔍

Publication Profile

ORCID

Education 🎓

Dr. Abdou earned his advanced degrees in mathematics and computational sciences from prestigious institutions, focusing on mathematical modeling and advanced numerical methods. His rigorous academic training underpins his innovative research in applied mathematics and integral equations. 🧮

Experience 🏫

Dr. Abdou has an extensive career in academia and research, serving in various roles as a professor, mentor, and collaborator. He has contributed to international conferences, workshops, and academic journals, sharing his insights on integral and differential equations. His work also includes developing new mathematical models and algorithms applied in physics, engineering, and computational sciences. 🌐📖

Research Interests 🔬

Dr. Abdou’s research interests include:

Numerical methods for solving nonlinear integral equations. Fractional calculus and its applications. Thermoelasticity with double porosity. Spectral relationships for integral equations. Computational methods in applied mathematics 🚀📈

Awards and Recognitions 🏆

Dr. Abdou has been acknowledged for his outstanding contributions to mathematics and computational sciences, receiving numerous accolades for his publications, including recognition in prestigious international journals. His research has garnered significant attention and citations, reflecting the impact of his work in the mathematical community. 🌟🎖️

Publications 📜

A Computational Method for Solving Nonlinear Fractional Integral Equations

An Algorithm for the Solution of Integro-Fractional Differential Equations with a Generalized Symmetric Singular Kernel

Numerical Simulation, Existence, and Uniqueness for Solving Nonlinear Mixed Partial Integro-Differential Equations with Discontinuous Kernels

Thermopotential Function in Position and Time for a Plate Weakened by Curvilinear Hole

On an Approximate Solution of a Boundary Value Problem for a Nonlinear Integro-Differential Equation

 

VIOREL PAUNOIU | Reverse Engineering | Best Researcher Award

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Prof. Dr. VIOREL PAUNOIU | Reverse Engineering | Best Researcher Award

Prof dr.eng.habil. UNIVERSITY DUNAREA DE JOS OF GALATI, Romania

Prof. Viorel Paunoiu is a distinguished scholar in Manufacturing Engineering at “Dunarea de Jos” University of Galati, Romania, where he has been a faculty member since 1987. Known for his innovative research in sheet metal forming and kinetic control methods for manufacturing, he contributes significantly to advancing industrial engineering processes. 📐 His work often explores reverse engineering and the optimization of manufacturing systems, helping improve quality and efficiency in the automotive and machinery sectors.

Publication Profile

ORCID

🎓 Education

Prof. Paunoiu holds extensive academic and professional expertise developed over several decades, contributing meaningfully to Engineering Sciences. His education and research continually elevate the field of manufacturing engineering. 🎓📈

💼 Experience

With over 30 years at “Dunarea de Jos” University, Prof. Paunoiu has led research projects, published extensively in mechanics and applied sciences, and collaborated on transformative industrial applications. His experience spans reverse engineering, sheet metal forming, and kinetic control, underscoring his role as a leader in manufacturing research. 🏛️

🔍 Research Interests

Prof. Paunoiu’s research interests focus on sheet metal stamping, kinetic control in forming processes, and reverse engineering in manufacturing. His work emphasizes innovative approaches to improve process quality and component precision in industrial settings. 🧩🔬

🏆 Awards

Prof. Paunoiu has been recognized for his impactful contributions to manufacturing engineering, helping bridge academia and industry through his advancements in kinetic control and reverse engineering. 🌟

📚 Publications

“Contribution to the formability improvement in sheet metal stamping by a novel technique to control press kinetics”
Journal: Mechanics & Industry
Year: 2024
DOI: 10.1051/meca/2024015
Cited by: Crossref

“Reverse Engineering Used to Profile a Gerotor Pump Rotor”
Journal: Applied Sciences
Year: 2023
DOI: 10.3390/app131911069
Cited by: Crossref

“Contribution to a new method for deep drawing with kinetic control”
Journal: MATEC Web of Conferences
Year: 2022
DOI: 10.1051/matecconf/202236801022
Cited by: Crossref

“Quality characteristics analysis for the assembly of the elements from the construction of a mechanism for adjusting the seats in the automotive industry”
Journal: MATEC Web of Conferences
Year: 2022
DOI: 10.1051/matecconf/202236801011
Cited by: Crossref

“Study of the enwrapping of the front profiles of the active elements of a three-screw compressor”
Journal: MATEC Web of Conferences
Year: 2022
DOI: 10.1051/matecconf/202236801003
Cited by: Crossref

 

Naeem Saleem | Nonlinear Analysis | Best Researcher Award

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Assoc. Prof. Dr. Naeem Saleem | Nonlinear Analysis | Best Researcher Award

Associate Professor, Department of Mathematics, University of Management and Technology, Lahore, Pakistan

🌍 Dr. Naeem Saleem is a dedicated mathematician from Pakistan, currently serving as an Associate Professor in Mathematics at the University of Management and Technology in Lahore. With over a decade of academic experience, Dr. Saleem has made notable contributions to fixed-point theory, approximation theory, and mathematical analysis, focusing on advanced iterative methods and contraction mappings. His work has been published in esteemed international journals, reflecting his commitment to the advancement of mathematical knowledge.

Publication Profile

Google Scholar

Education

🎓 Dr. Saleem completed his Ph.D. in Mathematics from the University of Management and Technology, Lahore, in 2017. Prior to that, he earned his MS/M.Phil in Mathematics from the National University of Computer and Emerging Sciences in 2011, following an M.Sc. in Mathematics from the University of Punjab, Lahore, in 2007.

Experience

📘 Dr. Saleem has held academic positions at the University of Management and Technology, serving as an Assistant Professor from 2012 to 2020 and, since 2020, as an Associate Professor. He continues to mentor students in advanced mathematics and contributes to the university’s research initiatives in mathematical sciences.

Research Interests

🔬 Dr. Saleem’s research centers on fixed-point theory, non-linear functional analysis, fractal theory, and applications of contractive mappings in metric spaces. His recent publications include work on generalized contractions, split feasibility problems, and approximation theories in convex metric spaces.

Publications

“Common Attractors of Generalized Hutchinson–Wardowski Contractive Operators”
📅 Fractal and Fractional (2024-11-09)
DOI: 10.3390/fractalfract8110651

“Intuitionistic Fuzzy Z-Contractions and Common Fixed Points with Applications”
📅 European Journal of Pure and Applied Mathematics (2024-10-31)
DOI: 10.29020/nybg.ejpam.v17i4.5431

“Approximation Theorems for G-Nonexpansive Mappings in Convex Metric Spaces by Three-Step Iterations”
📅 Alexandria Engineering Journal (2024-09)
DOI: 10.1016/j.aej.2024.05.067

“Strong and Weak Convergence Theorems for the Split Feasibility Problem of (β,k)-Enriched Strict Pseudocontractive Mappings with an Application in Hilbert Spaces”
📅 Symmetry (2024-05-02)
DOI: 10.3390/sym16050546

“Approximating Fixed Points of Weak Enriched Contractions Using Kirk’s Iteration Scheme of Higher Order”
📅 OpenAlex (2024-02-14)
DOI: 10.60692/hhz1x-y7n62

Gia SIRBILADZE | Fuzyt Dynamic Systems | Best Researcher Award

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Prof. Gia SIRBILADZE | Fuzyt Dynamic Systems | Best Researcher Award

Prof., Ivane Javakhishvili Tbilisi State University (Georgia), Georgia

🌟 Professor Gia Sirbiladze is a prominent figure in intelligent simulation modeling and decision-making in uncertain environments, with over 40 years of teaching and research experience. Currently, he serves as a Professor of Applied Informatics at the Department of Computer Sciences at Iv. Javakhishvili Tbilisi State University (JTSU) in Georgia. 📘 As an author and editor of more than 150 papers and two monographs, he has made significant contributions to expert knowledge engineering and fuzzy technologies in decision-support systems. Additionally, Professor Sirbiladze is a member of several international computer science societies, including IEEE, WSEAS, IFSR, and MCDM, and sits on the editorial boards of multiple international journals. 🌐

Publication Profile

ORCID

Education

🎓 Professor Sirbiladze holds a deep-rooted academic background in computer science and applied informatics, specializing in systems science, fuzzy technologies, and decision-making.

Experience

📚 With over four decades of experience at JTSU, Professor Sirbiladze has shaped research and teaching in applied informatics and computer sciences, especially within intelligent modeling and complex decision-making problems.

Research Interests

🔍 His research interests span several advanced areas of computer science, including systems science and engineering, fuzzy technologies, decision-support systems, control and filtration of extreme dynamic systems, and fuzzy discrete optimization in management.

Awards

🏅 Professor Sirbiladze has been recognized for his exceptional contributions to intelligent systems and decision-making, earning honors in his field and serving on editorial boards of international journals.

Publications

“Divergence and Similarity Characteristics for Two Fuzzy Measures Based on Associated Probabilities”
Published in: Axioms – 2024-11-09
DOI: 10.3390/axioms13110776

“Associated Probabilities in Insufficient Expert Data Analysis”
Published in: Mathematics – 2024-02-07
DOI: 10.3390/math12040518

“Possibilistic Simulation-Based Interactive Fuzzy MAGDM Under Discrimination q-Rung Picture Linguistic Information: Application in Educational Programs Efficiency Evaluation”
Published in: Engineering Applications of Artificial Intelligence – 2023-08
DOI: 10.1016/j.engappai.2023.106278

“Associated Probabilities Aggregations in Multistage Investment Decision-Making”
Published in: Kybernetes – 2023-03-24
DOI: 10.1108/K-09-2021-0908

Fida Ullah | Natural language Processing | Data Science Contribution Award

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Mr.Fida Ullah | Natural language Processing | Data Science Contribution Award

PhD Student, Institute of politechnical National, Mexico

🎓 Fida Ullah is a dedicated PhD student in Computer Science at Instituto Politécnico Nacional, Mexico, specializing in Named Entity Recognition (NER) and machine learning, with a deep passion for advancing Natural Language Processing (NLP) for low-resource languages. His expertise spans deep learning and transformer models, and he is skilled in applying these techniques to various text analysis challenges. Fida has published extensively in reputable journals and actively engages in the latest NLP developments, making him a promising researcher in this field.

Publication Profile

Google Scholar

Education

📘 PhD in Computer Science – Instituto Politécnico Nacional, Mexico (2022-Present), Thesis: Urdu Named Entity Recognition with Deep Learning
Advisor: Dr. Alexander Gelbukh. M.Sc. in Computer Science – Beijing University of Chemical Technology, China (2018-2021)

Experience

💻 Fida has hands-on experience with Python and essential machine learning libraries like TensorFlow, PyTorch, and Keras. He has worked extensively with deep learning frameworks, focusing on Named Entity Recognition, sentiment analysis, and hate speech detection in low-resource languages. His work has been showcased at international conferences, and he has collaborated with global researchers on NLP projects.

Research Interests

🔍 Fida’s research interests are centered around Natural Language Processing and Named Entity Recognition for low-resource languages, utilizing deep learning, transformer models, and data augmentation techniques. He is also intrigued by advancing explainable machine learning applications for smart city innovations.

Awards and Achievements

🏆 Awards include the CONACYT Scholarship (Mexico) and the Chinese Government Scholarship for his academic excellence and contributions to NLP research.

Publications

Ullah, Fida, Ihsan Ullah, and Olga Kolesnikova. “Urdu Named Entity Recognition with Attention Bi-LSTM-CRF Model.” Mexican International Conference on Artificial Intelligence (2022). Springer Nature Switzerland.

Fida Ullah, Alexander Gelbukh, MT Zamir, EM Felipe Revoron, and Grigori Sidorov. “Enhancement of Named Entity Recognition in Low-Resource Languages with Data Augmentation and BERT Models: A Case Study on Urdu.” Computers, MDPI (2023). https://doi.org/10.3390/computers13100258.

Muhammad Arif, MS Tash, Ainaz Jamshidi, Fida Ullah, et al. “Analyzing Hope Speech from Psycholinguistic and Emotional Perspectives.” Scientific Reports (2024). https://doi.org/10.1038/s41598-024-74630-y.

Fida Ullah, M.Ahmed, MT. Zamir, et al. “Optimal Scheduling for the Performance Optimization of SpMV Computation using Machine Learning Techniques.” IEEE Xplore (2024). https://doi.org/10.1109/ICICT62343.2024.00022.

Alberto Martínez Castro, Jesús, et al. “Suppressor of Cytokine Signaling Members in Lung Adenocarcinoma: Unveiling Expression Patterns, Posttranslational Modifications, and Clinical Significance.” Journal of Population Therapeutics and Clinical Pharmacology 30, no. 18 (2023): 2077-2091.

 

Hsing-Chung Chen | Blockchain Technology | Best Researcher Award

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Prof. Dr. Hsing-Chung Chen | Blockchain Technology | Best Researcher Award

Distinguished Professor, Asia University, Taiwan

Prof. Hsing-Chung Chen is a Distinguished Full Professor at the Department of Computer Science and Information Engineering, Asia University, Taiwan. He holds a Ph.D. in Electronic Engineering from National Chung Cheng University, Taiwan (2007). A Senior Member of IEEE, he is recognized for his outstanding contributions to Information Security, Blockchain Technology, Internet of Things, Artificial Intelligence, and Cryptography. He has served in numerous academic and leadership roles, including Director of the Information Security Research Center at Asia University. Prof. Chen has been recognized on the “World Ranking of Top 2% Scientists” by Stanford University for four consecutive years (2021-2024). Additionally, he has been awarded the Best Paper and Best Post Publication awards and has published 80 journal papers, 6 patents (including 2 US Patents), and over 130 conference papers.

Publication Profile

ORCID

Education 🎓

Prof. Hsing-Chung Chen received his Ph.D. in Electronic Engineering from National Chung Cheng University, Taiwan, in 2007, laying the foundation for his extensive career in information security, blockchain, and related fields.

Experience 🧑‍🏫

Prof. Chen began his academic career as an Assistant Professor at Asia University, Taiwan, in 2008, advancing to Associate Professor and Full Professor until he was named Distinguished Full Professor in 2019. He has held various leadership positions, including Chairman of the Department of Computer Science and Information Engineering at Asia University and Research Consultant at China Medical University Hospital. He has been a key figure in organizing major conferences and workshops and serving on editorial boards for prestigious international journals.

Research Interests 🔍

His research interests are wide-ranging and include Information and Communication Security, Software Supply Chain, Blockchain Technology, Internet of Things (IoT), Mobile Networks, Medical Signal Image Processing, AI & Soft Computing, and Applied Cryptography.

Awards 🏆

Prof. Chen has received numerous prestigious awards, including the Best Paper Awards at BWCCA 2016, MobiSec 2017, and BWCCA 2018, as well as the Best Journal Paper Award from AACT. He has also been honored with multiple recognitions, such as the ACM ICFET 2020 Best Paper Presentation Award and the TANET 2018 Best Post Publication Award.

Publications 📚

“A Blockchain-Based IoT Security Architecture for Digital Healthcare”
Published in IEEE Access (2023)
Link to Publication
Cited by: 50+

“Secure Mobile and Wireless Network Protocols”
Published in Journal of Internet Services and Information Security (2022)
Link to Publication
Cited by: 30+

“AI-Driven Cryptographic Techniques for Smart Healthcare Systems”
Published in IEEE Transactions on Industrial Informatics (2021)
Link to Publication
Cited by: 75+

“Data Security in IoT Networks: A Blockchain Approach”
Published in International Journal of Engineering and Industries (2020)
Link to Publication
Cited by: 45+

“Mobile and Wireless Network Security: Challenges and Solutions”
Published in Journal of Advanced Transportation (2019)
Link to Publication
Cited by: 60+

 

Jun Wu | network security | Best Researcher Award

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Dr. Jun Wu | network security | Best Researcher Award

Lecturer, Hangzhou Dianzi University, China

Jun Wu is a dedicated lecturer at Hangzhou Dianzi University, known for his extensive research in information and communication engineering. With a Ph.D. from Southeast University, China, he has significantly contributed to advancements in wireless communication. Over the years, Jun has authored more than 80 publications and actively engages in impactful research areas like cognitive radio networks, machine learning, and network security.

Publication Profile

ORCID

🎓 Education:

Jun Wu earned his Ph.D. in Information and Communication Engineering from Southeast University in Nanjing, China, in 2018. This foundation has propelled his expertise in fields such as spectrum sensing and drone technologies.

💼 Experience:

As a lecturer at the School of Communication Engineering, Hangzhou Dianzi University, Jun has not only contributed to academia with numerous publications but also spearheaded several research projects and patent applications. His editorial role for Sensors journal showcases his commitment to furthering research in wireless sensor networks.

🔬 Research Interests:

Jun’s research interests include spectrum sensing and management, drone trajectory optimization, cognitive radio networks, wireless sensor networks, machine learning, and network security. His work emphasizes innovative solutions for the evolving Internet of Things (IoT) and unmanned aerial vehicle (UAV) technologies.

🏆 Awards:

Jun Wu’s dedication to research has garnered him recognition within the academic community, and his contributions through over 80 papers, 18 patents, and editorial roles reflect his impact. His influence is evidenced by his publications’ 542 citations and an H-index of 13.

Publications

“Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things”
Published in Prime Archives in Sensors, 3rd Edition (Vide Leaf), Link to publication

“Spectrum Sensing and Access Technologies for Drones” (Guest Editor)
Special Issue in Sensors, View here

Erhan Deniz | Complex Analysis | Best Researcher Award

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Prof. Dr. Erhan Deniz | Complex Analysis | Best Researcher Award

Academician, Kafkas University, Turkey

Professor Dr. Erhan Deniz is a dedicated academician in mathematics, currently serving as a Full Professor at Kafkas University, Turkey. With extensive experience in mathematical research, he is highly recognized for his contributions to univalent and special functions, areas critical to applications in mathematical physics, biology, and fluid mechanics. His work spans various collaborative projects and has been widely cited, establishing him as an influential figure in the field.

Publication Profile

Google Scholar

🎓 Education

Undergraduate: Mathematics, Atatürk University (2004) 🎓, MSc: Mathematics, Kafkas University (2007) 📘, Ph.D.: Mathematics, Atatürk University (2011) 🧑‍🎓

💼 Experience

Professor Dr. Deniz’s academic career began as a Research Assistant at Kafkas University in 2005, followed by roles at Atatürk University. Since 2018, he has held the position of Full Professor at Kafkas University, actively contributing to research in analytic and univalent functions, harmonic functions, and more. His research impact includes managing several university-backed research projects and publishing widely cited journal articles.

🔬 Research Interests

Professor Deniz’s research focuses on univalent functions, special functions (e.g., Bessel, Lommel, Ramanujan functions), hypergeometric functions, Loewner theory, and multivalent functions. His work in these fields contributes significantly to areas such as mathematical physics, fluid mechanics, and mathematical chemistry.

🏆 Awards

Professor Dr. Deniz has been nominated for the Best Researcher Award by the Computer Scientists Awards for his outstanding research contributions, impactful publications, and dedication to advancing mathematics.

📚 Publications

Here is a selection of publications authored by Professor Dr. Erhan Deniz:

Kazımoğlu, S., Dutta, H., & Deniz, E. (2024). Sufficient Conditions for Generalized Integral Operators Involving the Rabotnov Function. In B.C. Tripathy, H. Dutta, S.K. Paikray, B.B. Jena (Eds.), Operators, Inequalities and Approximation. Springer, Singapore. Link to publication

Numerous articles published in journals such as Hacet. J. Math. Stat., Appl. Math. Comput., Czech Math. J., J. Inequal. Appl., Math. Comput. Modelling, Analele Stiintifice ale Universitatii Ovidius Constanta, Comput. Math. Appl., and many more. His work is cited across databases like SCI, Scopus, and MathSciNet.

Khaled Mehrez | Special functions | Best Researcher Award

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Prof. Khaled Mehrez | Special functions | Best Researcher Award

University Tunis El Manar, Tunisia

Khaled Mehrez is an accomplished Assistant Professor at the Kairouan Preparatory Institute for Engineering Studies, University of Kairouan, Tunisia, since 2020. With a Habilitation in mathematics from the same institution, he has dedicated his career to advancing mathematical education and research. 🔍🎓

Publication Profile

Google Scholar

Khaled Mehrez is an accomplished Assistant Professor at the Kairouan Preparatory Institute for Engineering Studies, University of Kairouan, Tunisia, since 2020. With a Habilitation in mathematics from the same institution, he has dedicated his career to advancing mathematical education and research. 🔍🎓

Education

Khaled holds a Habilitation in Mathematics (2023) from the Kairouan Preparatory Institute for Engineering Studies, a Ph.D. in Mathematics (2017) from the Faculty of Mathematical, Physical and Natural Sciences of Tunis, a Master’s in Mathematics (2009), and a Bachelor’s in Mathematics (2006), both from the Faculty of Sciences of Bizerte. His academic journey began with a Baccalaureate in Mathematics from the High School of Kesra (2002). 📚🧮

Experience

Before joining the University of Kairouan, Khaled worked as a Contract Assistant at the Preparatory Institute for Engineering Studies of Monastir (2009-2013) and as an Assistant at the Higher Institute of Applied Sciences and Technologies of Kasserine (2013-2020). He has progressively advanced in his academic career, currently holding the position of Associate Professor at the Kairouan Preparatory Institute for Engineering Studies since July 2024. 🏫📈

Research Interests

Khaled’s research interests encompass special functions for engineers, including the Mittag-Leffler function, Gamma function, and Generalized Zeta function. He also delves into harmonic analysis with a focus on Dunkl and Weinstein theories, as well as geometric function theory, exploring concepts like univalence, starlike functions, and convexity. His work extends to applied mathematics. 📊🔬

Publications

Khaled Mehrez has contributed significantly to mathematical literature. Here are some of his notable publications:

K. Mehrez, Redheffer type inequalities for modified Bessel functions, Arab. J. Math. Sci., 22 (2016), 38–42.

K. Mehrez, Some New Wilker and Generalized Lazarević Type Inequalities for Modified Bessel Functions, Turkish Journal of Analysis and Number Theory, 4 (6) (2016), 168–171.

S. M. Sitnik, K. Mehrez, Proofs of some conjectures on monotonicity of ratios of Kummer, Gauss and generalized hypergeometric functions, Analysis, 36 (4) (2016), 263–268.

K. Mehrez, S. M. Sitnik, On monotonicity of ratios of some q-hypergeometric functions, Math. Vesnik, 68 (3) (2016), 225–231.

S. M. Sitnik, K. Mehrez, On monotonicity of ratios of some hypergeometric functions, Siberian Electronic Mathematical Reports, 13 (2016), 260-268.

 

Sara Tehsin | Deep learning | Best Researcher Award

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Ms. Sara Tehsin | Deep learning | Best Researcher Award

PhD Student, National University of Sciences and Technology, Islamabad, Pakistan

Sara Tehsin is a motivated and results-driven professional with over ten years of experience in Image Processing and Machine Learning. As an Engineering Lecturer at HITEC University in Taxila, Pakistan, she excels in delivering high-quality educational experiences and has a proven track record of producing outstanding results through her strong work ethic, adaptability, and effective communication skills. She is passionate about academic development and seeks opportunities to contribute her expertise while furthering her professional growth. 📚💻

Publication Profile

Google Scholar

Education

Sara Tehsin is currently pursuing a PhD in Computer Engineering at the National University of Sciences and Technology (NUST), Islamabad, where she has achieved a remarkable GPA of 3.83/4.00. Her research focuses on Digital Forensics, Deep Learning, and Digital Image Processing. She holds a Master’s degree in Computer Engineering from NUST, where she graduated with a GPA of 3.7/4.0, and a Bachelor’s degree from The Islamia University of Bahawalpur, with a GPA of 3.36/4.00. 🎓🌟

Experience

Sara has extensive teaching experience, currently serving as an Engineering Lecturer at HITEC University since September 2019, where she develops engaging curriculum and delivers lectures aligned with international standards. Previously, she was a Computer Science Lecturer at Sharif College of Engineering and Technology, and she also served as a Teaching Assistant at NUST and a Lab Engineer at Foundation University. Her roles have encompassed curriculum development, practical instruction, and student support in various computer science subjects. 👩‍🏫🔧

Research Interests

Sara’s research interests encompass Digital Forensics, Deep Learning, Digital Image Processing, and Machine Learning. She focuses on developing innovative solutions for image recognition and forgery detection, contributing significantly to the fields of computer vision and machine learning. Her work aims to enhance the accuracy and efficiency of image processing systems. 🧠🔍

Publications

Self-organizing hierarchical particle swarm optimization of correlation filters for object recognition
S. Tehsin, S. Rehman, M.O.B. Saeed, F. Riaz, A. Hassan, M. Abbas, R. Young, …
IEEE Access, 5, 24495-24502 (2017)
Cited by: 21

Improved maximum average correlation height filter with adaptive log base selection for object recognition
S. Tehsin, S. Rehman, A.B. Awan, Q. Chaudry, M. Abbas, R. Young, A. Asif
Optical Pattern Recognition XXVII, 9845, 29-41 (2016)
Cited by: 18

Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments
S. Tehsin, S. Rehman, F. Riaz, O. Saeed, A. Hassan, M. Khan, M.S. Alam
Pattern Recognition and Tracking XXVIII, 10203, 28-39 (2017)
Cited by: 12

Comparative analysis of zero aliasing logarithmic mapped optimal trade-off correlation filter
S. Tehsin, S. Rehman, A. Bilal, Q. Chaudry, O. Saeed, M. Abbas, R. Young
Pattern Recognition and Tracking XXVIII, 10203, 22-37 (2017)
Cited by: N/A