Yaser Azimi | Artificial Intelligence | Best Researcher Award

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Yaser Azimi | Artificial Intelligence | Best Researcher Award

Assistant Professor at  Urmia University, Iran 

Yaser Azimi is a distinguished professional in the field of [specific field or industry], recognized for his contributions to [specific contributions or notable projects]. With a robust academic background and extensive experience, he has made significant strides in [relevant aspects of his work]. His dedication to advancing knowledge and practice in his field makes him a respected figure among peers and students alike.

 

Professional Profile 

🎓 Education

Yaser Azimi holds a [degree] in [field of study] from [University Name], where he graduated with [honors or notable achievements]. He furthered his education by obtaining a [higher degree] in [specialization] from [another University Name], focusing on [specific area of study]. His educational background has provided him with a solid foundation in [relevant skills or knowledge areas], which he applies in his professional endeavors.

🏢 Work Experience

With over [number] years of experience in [specific industry or field], Yaser has held various positions that have honed his skills and expertise. He began his career as a [first job title] at [Company/Organization Name], where he [briefly describe responsibilities and achievements]. Over the years, he has progressed to roles such as [list subsequent job titles and companies], contributing to projects that [describe notable projects or initiatives]. His diverse experience equips him to handle complex challenges in his field effectively.

🧬 Skills

Yaser possesses a wide array of skills that contribute to his success as a [profession]. His expertise includes [list relevant skills, e.g., data analysis, project management, research methodologies, etc.]. Additionally, he is proficient in [specific software, tools, or techniques], which enhances his capability to deliver high-quality work. His strong communication and leadership skills enable him to collaborate effectively with colleagues and guide teams toward achieving common goals.

Awards and Honors 🏆

Throughout his career, Yaser has been recognized with several awards and honors for his outstanding contributions. Notable accolades include [list specific awards, recognitions, or honors received], highlighting his commitment to excellence and innovation in his field. These recognitions reflect his dedication to advancing [specific aspects of his profession] and his impact on the community.

Membership 🤝

Yaser is an active member of several professional organizations, including [list relevant organizations or associations]. His involvement in these memberships allows him to stay updated on industry trends, network with fellow professionals, and contribute to the advancement of [specific field or profession]. His commitment to professional development is evident through his participation in [mention any committees, boards, or special initiatives].

Teaching Experience 📚

In addition to his professional work, Yaser has a passion for education and has served as a [teaching position, e.g., lecturer, professor] at [institution or organization]. His teaching experience includes courses on [specific subjects or topics], where he inspires students to explore [relevant concepts or areas]. He is known for his engaging teaching style and commitment to fostering a supportive learning environment.

🔬 Research Focus

Yaser’s research focuses on [specific areas of research or interest], aiming to [describe the goals or objectives of his research]. He has published numerous papers in esteemed journals and has presented his work at various conferences, contributing to the body of knowledge in [relevant field]. His research not only advances theoretical understanding but also has practical implications for [mention specific applications or industries].

📚 Publication 

  • Title: Mobility aware and energy-efficient federated deep reinforcement learning assisted resource allocation for 5G-RAN slicing
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2024
    Citations: 0
  • Title: Applications of Machine Learning in Resource Management for RAN-Slicing in 5G and beyond Networks: A Survey
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2022
    Citations: 23
  • Title: Energy-Efficient Deep Reinforcement Learning Assisted Resource Allocation for 5G-RAN Slicing
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2022
    Citations: 37
  • Title: Improvement of minimum disclosure approach to authentication and privacy in RFID systems
    Authors: M.H.F. Kordlar, Yaser Azimi
    Year: 2015
    Citations: 0
  • Title: Improvement of quadratic residues based scheme for authentication and privacy in mobile RFID
    Authors: Yaser Azimi, J. Bagherzadeh
    Year: 2015
    Citations: 3

Masoumeh Alinia | Artificial Intelligence | Best Researcher Award

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Ms Masoumeh Alinia |Artificial Intelligence | Best Researcher Award 🏆

student at Alzahra university,  Iran🎓

Masoumeh Alinia is a talented and driven professional with a dual background in Software and Electronic Engineering. With a focus on data science and deep learning, she has contributed to innovative projects across various sectors. Her expertise lies in recommender systems, machine learning models, and big data analysis. Passionate about technology and education, Masoumeh has experience teaching and mentoring students, while also pursuing impactful research in advanced machine learning techniques and IoT systems. Fluent in both Persian and English, she thrives on solving complex problems and continuously improving her technical and soft skills. 

Professional Profile 

Education

Masoumeh earned her Master of Science in Software Engineering from Alzahra University, Tehran, in 2024 with an impressive GPA of 18.57/20. Her thesis focused on collaborative filtering recommender systems using deep learning, supervised by Dr. Hasheminejad. She also holds an M.Sc. in Electronic Engineering from Shahid Beheshti University, where her thesis explored nanoscale spintronic technology for three-valued memory. She completed her Bachelor’s in Electronic Engineering from Technical and Vocational University with a GPA of 18.87/20. Throughout her academic journey, she excelled in both practical and theoretical fields.

Work Experience

Masoumeh worked as a Data Scientist at Afarinesh, a knowledge-based IT firm, from February to July 2023. There, she developed deep learning-based recommender systems using TensorFlow and designed various models like Neural Collaborative Filtering (CF), SVD, and NMF. She also managed relational databases, processed large datasets, and conducted A/B tests for performance evaluation. Masoumeh played a key role in enhancing data-driven decision-making processes within the company’s ecosystem of startups, contributing to projects like Sayeh platform and Boxel. Her experience spans technical model development and business-focused data analysis.

Skills & Competencies

Masoumeh is proficient in Machine Learning, Data Visualization, Database Management, and Model Deployment. She is skilled in programming languages such as Python, C#, C, VHDL, and Verilog, and works comfortably with frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras. Her key soft skills include Critical Thinking, Adaptability, and a strong Openness to Feedback. She has consistently demonstrated her ability to learn new technologies quickly, solve complex problems, and contribute to collaborative environments.

Awards & Honors

Masoumeh has contributed to major international conferences, presenting papers on advanced topics in deep learning and recommender systems. Her research, co-authored with Dr. Hasheminejad, was presented at the 13th International Conference on Computer and Knowledge Engineering, focusing on link prediction for recommendation systems. She also co-authored another paper on location-based deep collaborative filtering for IoT service quality prediction, which was presented at the 7th International IoT Conference. These recognitions highlight her innovative contributions to both academia and industry.

Membership & Affiliations

Throughout her academic and professional journey, Masoumeh has actively participated in research and technical communities. Her involvement in collaborative research groups led to valuable insights in areas such as deep learning, IoT, and complex dynamical networks. While no specific memberships are listed, her participation in international conferences and collaborations with academic advisors and peers indicates strong engagement with the scientific and technical community. Her work is grounded in research excellence and practical application.

Teaching Experience

Masoumeh has shared her knowledge by teaching various technical courses. She served as an instructor at Atrak Institute of Higher Education, where she taught electronics courses and microcontroller/microprocessor labs using tools like Proteus and Atmel Studio. She also worked as a teaching assistant for Electric Circuits and Logic Circuit courses under Dr. Ramin Rajaee at Shahid Beheshti University. Her passion for teaching has allowed her to guide and mentor students in understanding complex concepts, fostering a collaborative learning environment.

Research Focus

Masoumeh’s research centers on recommender systems, deep learning, and IoT technologies. Her thesis explored collaborative filtering using deep learning techniques, aiming to enhance recommendation accuracy. She has also worked on link prediction for recommender systems, leveraging machine learning algorithms such as GCN-GNNs for better user experience. Additionally, her research extends to Quality-of-Service predictions in IoT through location-based collaborative filtering, pushing the boundaries of how personalized recommendations and service quality can be optimized in data-driven environments.

📖Publications : 

  • Link Prediction for Recommendation based on Complex Representation of Items Similarities
    📅 2023 | 📰 13th International Conference on Computer and Knowledge Engineering (ICCKE)
    👩‍💻 Masoumeh Alinia
    🔗 DOI: 10.1109/ICCKE60553.2023.10326315
  • Location-Based Deep Collaborative Filtering for Quality of Service Prediction in IoT
    📅 2023 | 📰 7th International Conference on Internet of Things and Applications (IoT)
    👨‍💻 Author unspecified
    🔗 DOI: 10.1109/IoT60973.2023.10365357

JiaLi Zhu | Artificial Intelligence | Best Researcher Award

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Ms JiaLi Zhu | Artificial Intelligence | Best Researcher Award 🏆

Research Fellow at University of Naples Federico II , Italy🎓

Jiali Zhu is a Senior Algorithm Engineer at Alipay, Ant Group with expertise in machine learning and deep learning. She holds a Master’s degree in Computer Technology from Southeast University, completed in June 2023 . Since July 2023, Jiali has worked as a Machine Learning Algorithm Engineer at Ant Group’s Alipay, focusing on cutting-edge algorithm development .

Professional Profile

Education🎓

Jiali Zhu earned a Master’s degree in Computer Technology from Southeast University in June 2023. Her academic journey reflects a strong foundation in advanced computing and algorithm design.

💼Work Experience

In July 2023, she embarked on her professional career as a Machine Learning Algorithm Engineer at Ant Group’s Alipay. She now holds the title of Senior Algorithm Engineer, where she works on innovative projects in machine learning and AI applications.

 🛠️Skills

Jiali is skilled in machine learning, deep learning, medical imaging technologies, and multimodal language models. Her expertise spans advanced algorithm design, attention mechanisms, and quantitative susceptibility mapping.

🏆Awards and Honors

She is a nominee for the “Best Researcher Award,” acknowledging her significant contributions in the field of machine learning and medical imaging.

 Research Focus 🔬

Jiali’s research focuses on integrating deep learning with medical imaging. She has contributed to projects like MobileFlow, a multimodal LLM for mobile GUI agents, and DE-Net, a detail-enhanced MR reconstruction network.

 

📖Publications : 

  • DE-Net: Detail-enhanced MR reconstruction network via global-local dependent attention
    📅 Year: 2024
    📖 Journal: Biomedical Signal Processing and Control
    🧠 Authors: J. Zhu, D. Hu, W. Mao, J. Zhu, R. Hu, Y. Chen
  • MobileFlow: A Multimodal LLM For Mobile GUI Agent
    📅 Year: 2024
    📖 Journal: arXiv preprint (arXiv:2407.04346)
    🧠 Authors: S. Nong, J. Zhu, R. Wu, J. Jin, S. Shan, X. Huang, W. Xu
  • Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction
    📅 Year: 2022
    📖 Journal: Quantitative Imaging in Medicine and Surgery
    🧠 Authors: J. Du, Y. Ji, J. Zhu, X. Mai, J. Zou, Y. Chen, N. Gu

 

Obsa Gilo Wakuma | Artificial Intelligence | Best Researcher Award

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Dr Obsa Gilo Wakuma  | Artificial Intelligence | Best Researcher Award 

 Ass. Prof at Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated researcher and academician with a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, where his thesis focused on “Deep Learning Approaches for Efficient Domain Adaptation.” He holds an M.Sc. in Computer Science (CGPA: 3.78) and a B.Sc. in Computer Science (CGPA: 3.56) from Wallaga University, Ethiopia.Dr. Obsa Gilo Wakuma continues to contribute to the academic and research community with his expertise in deep learning and domain adaptation, leveraging his strong background in computer science and engineering to drive innovative solutions.

🎓 Education:

  • Ph.D. in Computer Science and Engineering, IIT Patna (2024)
  • M.Sc. in Computer Science, Wallaga University (2018)
  • B.Sc. in Computer Science, Wallaga University (2014)
  • XII Class, Sibu Sire Preparatory School (2010)
  • X Class, Sibu Sire High School (2008)

💼 Work Experience:

Dr. Wakuma began his professional journey as a Recorder at Wallaga University’s main Registrar in Oromia, Ethiopia, from October 2014 to June 2015. He then served as a Laboratory Technician at Wallaga University’s Shambu campus until February 2016. From February 2016 to September 2018, he worked as a Graduate Assistant (GA-II) at Wallaga University, eventually becoming a Lecturer from February 2019 to September 2019. From September 2019 to December 2023, he was a Research Scholar at IIT Patna.

📚 Research Focus:

Dr. Wakuma’s research primarily revolves around deep learning and domain adaptation. His notable publications include articles in prestigious journals such as Expert Systems with Applications, Pattern Analysis and Applications, IEEE Access, and the Journal of Visual Communication and Image Representation. His work often explores robust unsupervised deep sub-domain adaptation and optimal transport for image classification.

🛠️ Skills:

Dr. Wakuma possesses strong competencies in multiple languages, including English, Afaan Oromoo, and Amharic. His technical skills encompass programming languages such as Java, PHP, Python, C, C++, and R. He is proficient in databases like MySQL, PostgreSQL, HSQL, and SQLite, and has experience in web development using HTML, CSS, JavaScript, and Apache Web Server. Additionally, he is skilled in academic research, teaching, training, consultation, and community service.

Research and Publications

  1. Journal Articles: Published in prestigious journals such as “Expert Systems with Applications,” “Pattern Analysis and Applications,” “IEEE Access,” and “Journal of Visual Communication and Image Representation.” Topics covered include domain adaptation in sensor data, subdomain adaptation via correlation alignment, robust unsupervised deep sub-domain adaptation, and unsupervised sub-domain adaptation using optimal transport.
  2. Conference Proceedings: Presented at the IEEE 19th India Council International Conference (INDICON), discussing the integration of discriminate features and similarity preserving for unsupervised domain adaptation.

Conclusion

Given his strong academic background, extensive research publications, practical skills, and teaching experience, Obsa Gilo Wakuma is a highly suitable candidate for the Best Researcher Award. His contributions to the field of computer science, particularly in deep learning and domain adaptation, demonstrate a high level of expertise and impact, making him deserving of such recognition.

📜 Publications:

  • Unsupervised sub-domain adaptation using optimal transport
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Journal of Visual Communication and Image Representation (2023)
    🖼️🔄🚚
  • Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Pattern Analysis and Applications (2024)
    📊🔄🌐
  • Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation
    O. Gilo, J. Mathew, S. Mondal
    2022 IEEE 19th India Council International Conference (INDICON) (2022)
    📚🔍🤝
  • Kernelized Bures metric: A framework for effective domain adaptation in sensor data analysis
    O. Gilo, J. Mathew, S. Mondal
    Expert Systems with Applications (2024)
    📈🔄🔬
  • RDAOT: Robust Unsupervised Deep Sub-domain Adaptation through Optimal Transport for Image Classification
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    IEEE Access (2023)
    🖼️🔄🧠
  • Information Extraction For Afaan Oromo News Texts Using Hybrid Approach
    O. Gilo
    Journal of Innovation in Computer Science and Engineering (2019)
    📰🔍🇪🇹
  • Unified Domain Adaptation with Discriminative Features and Similarity Preservation
    O. Gilo, J. Mathew, S. Mondal
    (Journal/Conference not specified)
    🔄🌐🤝

Cicil Denny | AI and Machine Learning | Best Researcher Award |

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Mr Cicil Denny | AI and Machine Learning |  Best Researcher Award

Student/Member at Vellore Institute of Technology, Chennai ,India

🌟 Cicil Melbin Denny J is a versatile Data Analyst with a strong background in Artificial Intelligence, Machine Learning, and Software Engineering. With hands-on experience in programming languages like Python, Java, C++, and JavaScript, and advanced skills in AI, ML, and Deep Learning frameworks such as PyTorch and TensorFlow, Cicil excels in tackling complex data problems. Notably, he led a research project on Semantic Segmentation for Underwater Imagery (SUIM), achieving an impressive mIoU of 84.83%, which was published in the prestigious “Results in Engineering” journal. Cicil’s technical prowess extends to data analytics tools like MySQL and NoSQL, and he is adept at using PowerBI and Tableau for business insights. His proficiency in network administration, cloud services (AWS, Azure, Google Cloud), and cybersecurity underlines his comprehensive skill set. Recognized for his problem-solving attitude and effective communication skills, Cicil is well-equipped to contribute to product analysis and support, making him a valuable asset in any tech-driven environment. 📊💡🤖

professional profile:

📚 Education:

  • B.Tech in CSE with specialization in Artificial Intelligence and Machine Learning, CGPA: 8.25 (Completed 6 Semesters)
  • Higher Education (2019-20): Mathematics, Biology, CGPA: 8.38

💼 Work Experience:

  • Research Internship at Vellore Institute of Technology, Chennai (May 2023 – July 2023)
  • Worked on Semantic Segmentation for Underwater Imagery (SUIM) using Swin Transformer, ConvMixer, and UNet architectures. Achieved mIoU metrics of 84.83% and published in “Results in Engineering” Journal – 2024 by Elsevier.

🔍 Skills:

  • Programming Languages: Python, Java, C++, C, JavaScript, PHP
  • Data Analytics: MySQL, NoSQL, PowerBI, Tableau
  • AI & ML: PyTorch, TensorFlow, Machine Learning, Deep Learning, Computer Vision
  • Software Engineering: DevOps, Software Design and Debugging, Test Development
  • Networking: TCP/IP, DNS, DHCP, VLANs, VPNs, Firewalls
  • Virtualization & Cloud: VMware, VirtualBox, AWS, Azure, Google Cloud
  • Other Tools: Jupyter Notebook, MATLAB, LTspice, CISCO, Unity Engine, MS Excel

🏆 Certifications:

  • TensorFlow Developer Certificate (2023: Zero to Mastery)
  • Deep Learning A-Z™ 2023: Neural Networks, AI & ChatGPT Bonus
  • Artificial Intelligence Analyst – IBM
  • Introduction to Artificial Intelligence – LinkedIn Learning
  • Artificial Intelligence – Verzeo
  • Introduction to Financial Modeling
  • Digital Marketing Fundamentals with Live Projects
  • The A-Z Digital Marketing Course

🔬 Research Focus:

  • 🔬 Cicil Melbin Denny J’s research focuses on cutting-edge technologies in AI and Machine Learning. He has extensively worked on Semantic Segmentation for Underwater Imagery using advanced architectures like Swin Transformer, ConvMixer, and UNet, achieving high accuracy. His work on IoT botnet detection leverages autoencoders, LSTM-CNN, and DNN to enhance cybersecurity. Additionally, he explores route mapping algorithms, blockchain technology, and cryptocurrency trends. Cicil’s dedication to innovation is evident through his projects on malware detection using ML algorithms and IoT-based accident intimation systems, aiming to improve safety and security in various domains. 🌊🤖🔒🌐

👩‍🏫 Teaching & Knowledge Sharing:

  • Advanced skills in AI, ML, Deep Learning, and Computer Vision with hands-on experience.
  • Prepared detailed reports and suggested improvements on QA patterns for Amazon Warehouses.

 

publications🌟

Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award

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Dr Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award 

Associate Professor at  SR University Warangal India

Dr. Nafis Uddin Khan is an esteemed academic and researcher specializing in Information and Communication Technology. With a Ph.D. from the Atal Bihari Vajpayee – Indian Institute of Information Technology & Management, Gwalior, he has a profound expertise in computer vision, image processing, and fuzzy logic applications in signal and image processing. He currently serves as an Associate Professor at SR University Warangal.

Education 📚

  • Ph.D. in Information and Communication Technology from Atal Bihari Vajpayee – Indian Institute of Information Technology & Management, Gwalior, India (2013).
  • M.Tech in Software Systems from Samrat Ashok Technological Institute, Vidisha, under Rajiv Gandhi Prodyogiki Vishwavidyalaya, Bhopal, India (2008).
  • B.E. in Electronics & Telecommunication Engineering from Jawaharlal Darda Institute of Engineering & Technology, Yavatmal, under Amravati University, Amravati, India (2003).
  • H.S.S.C. from Tiny Tots E. M. H. S. School, Seoni, M.P. Board, India (1997).
  • H.S.C. from Gyan Jyoti E. M. H. S. School, Nainpur, M.P. Board, India (1995).

Work Experience 💼

  1. Associate Professor, School of CS & AI, SR University Warangal, Telangana, India (since August 2023).
  2. Assistant Professor (Senior Grade), Jaypee University of Information Technology, Solan, Himachal Pradesh, India (2017-2023).
  3. Assistant Professor (Senior Grade), Jaypee University of Engineering and Technology, Raghogarh, Madhya Pradesh, India (2013-2017).
  4. Lecturer, Anand Engineering College, Agra, Uttar Pradesh, India (2008-2009).
  5. Lecturer, Hitkarini College of Engineering and Technology, Jabalpur, Madhya Pradesh, India (2004-2005).

Skills & Certifications 💡

  • Programming: Matlab, C, C++, Python.
  • Technical Writing
  • Team Work and Leadership

Administrative Roles 🏢

  • Associate Dean – Admissions, SR University, Warangal (since January 2024).
  • Training and Placement – Faculty Coordinator, Jaypee University of Information Technology, Solan (2017-2023).
  • Coordinator of Student Activities and Placement Section in Internal Quality Assurance Cell (IQAC), Jaypee University of Information Technology, Solan (2017-2023).

Research Focus 🔬

  • Statistical Image Processing
  • Medical Image Processing
  • Fuzzy Logic based Applications in Signal and Image Processing
  • Soft Optimization Techniques in Signal and Image Processing

Professional Contributions 📈

  • Enhanced sharp edge features and reduced Gaussian noise using singular value decomposition on optimal anisotropic diffused images.
  • Developed a fuzzy-based diffusion coefficient function for selective smoothing of impulsive noise.
  • Explored soft computing-based optimization techniques for speckle reduction in medical ultrasound and X-ray images.

Workshops and Conferences 🗓️

  • Coordinated multiple workshops and short-term programs on AI, signal processing, and leadership in education.
  • Served as an Invited Session Chair and Organizing Committee Member in various international conferences, including the IEEE International Conference on Signal Processing, Computing and Control.

Memberships 🤝

  • Active participation in academic and professional organizations through organizing and coordinating roles in numerous conferences and workshops.

 

Publications 📚

  1. Fuzzy C-Means Clustering Based Selective Edge Enhancement Scheme for Improved Road Crack Detection 🛤️
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V.
    • Journal: Engineering Applications of Artificial Intelligence
    • Year: 2024
  2. Fuzzy Based Self-Similarity Weight Estimation in Non-Local Means for Gray-Scale Image De-Noising 🖤
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Journal: Digital Signal Processing: A Review Journal
    • Year: 2024
  3. Road Crack Detection Using Pixel Classification and Intensity-Based Distinctive Fuzzy C-Means Clustering 🛤️
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V.
    • Journal: Visual Computer
    • Year: 2024
  4. A Comparative Survey on Histogram Equalization Techniques for Image Contrast Enhancement 📊
    • Authors: Malik, A., Khan, N.U.
    • Journal: Lecture Notes in Electrical Engineering
    • Year: 2024
  5. A Two Phase Ultrasound Image De-Speckling Framework by Nonlocal Means on Anisotropic Diffused Image Data 🩺
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Journal: Informatica (Slovenia)
    • Year: 2023
  6. An Efficient Fuzzy Inference System Based Approximated Anisotropic Diffusion for Image De-Noising 🖥️
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Journal: Cluster Computing
    • Year: 2022
  7. Digital Image Enhancement and Reconstruction 📘
    • Authors: Rajput, S.S., Khan, N.U., Singh, A.K., Arya, K.V.
    • Journal: Digital Image Enhancement and Reconstruction
    • Year: 2022
  8. Brain Tumor Image Segmentation Using K-Means and Fuzzy C-Means Clustering 🧠
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V., Vishwakarma, S.K., Bashar, A.
    • Journal: Digital Image Enhancement and Reconstruction
    • Year: 2022
  9. Improved Road Crack Detection Using Histogram Equalization Based Fuzzy-C Means Technique 🛤️
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V.
    • Conference: PDGC 2022 – 7th International Conference on Parallel, Distributed and Grid Computing
    • Year: 2022
  10. Cuckoo Search Optimized Histogram Equalization for Low Contrast Image Enhancement 🐦
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Conference: PDGC 2022 – 7th International Conference on Parallel, Distributed and Grid Computing
    • Year: 2022