Saulius Baskutis | Manufacturing Applications | Excellence in Computer Vision Award

Published on by Computer Vision Awards

Prof. Dr. Saulius Baskutis | Manufacturing Applications | Excellence in Computer Vision Award

Professor at Kaunas University of Technology | Lithuania

Prof. Dr. Saulius Baskutis is a distinguished academic and researcher whose career spans decades of teaching, research, and industrial engagement in the field of engineering sciences. He has contributed significantly to the advancement of materials testing, welding processes, coatings, renewable energy, logistics, and device diagnostics, while also actively participating in collaborative international projects. His professional journey reflects a balance between academic excellence and industrial practice, providing him with the ability to develop innovative, practical solutions for technological challenges. With numerous publications in reputable, indexed journals and presentations at international conferences, he has built a strong scholarly reputation. His leadership in EU-funded projects and membership in professional associations highlights his influence in both academic and professional communities. Recognized for his commitment to advancing science and technology, he continues to inspire students, researchers, and industry experts, while shaping the future of sustainable engineering practices through impactful research and collaborations.

Professional Profiles 

Scopus Profile | ORCID Profile 

Education

Prof. Dr. Saulius Baskutis began his academic journey at Kaunas Polytechnical Institute, where he earned an engineering qualification and later pursued doctoral studies in technical sciences, which shaped the foundation of his research career. His academic training combined deep theoretical knowledge with applied aspects of mechanical and material sciences, enabling him to explore innovative solutions in manufacturing and energy systems. During his postgraduate years, he developed expertise in welding, coatings, and materials testing, areas that would remain central to his research. He later expanded his knowledge through continuous professional development and specialized training programs across Europe, focusing on Industry 4.0, renewable energy, mechatronics, and advanced manufacturing technologies. This commitment to lifelong learning has strengthened his academic portfolio and ensured that his teaching and research remain aligned with evolving industrial needs. His education reflects a continuous pursuit of excellence, integrating traditional engineering knowledge with modern approaches to meet current and future challenges.

Professional Experience

Prof. Dr. Saulius Baskutis has built an impressive professional career combining academia and industry, demonstrating strong leadership and applied expertise in engineering. He has served at Kaunas University of Technology in various roles, progressing from assistant and lecturer to associate professor and professor, contributing extensively to teaching and curriculum development in manufacturing and mechanical engineering. His professional journey is enriched by industrial experience with organizations in Lithuania, Denmark, and Finland, where he worked as an engineer, manager, and project leader. These positions enabled him to apply academic insights to solve real-world engineering problems while fostering stronger connections between research and practice. He has also held leadership roles in European and national research projects, demonstrating the ability to guide interdisciplinary teams and achieve impactful outcomes. His active participation in Erasmus programs and scientific exchanges further broadened his expertise, while his engagement in professional associations has extended his influence within the engineering community.

Research Interest

Prof. Dr. Saulius Baskutis has a diverse range of research interests that reflect his commitment to addressing technological and societal challenges through engineering innovations. His primary focus lies in materials testing, welding processes, and coatings, where he investigates methods to improve durability, performance, and cost-effectiveness in industrial applications. He is also actively engaged in exploring renewable energy sources, with particular attention to sustainable energy production, district heating systems, and the integration of green technologies into industrial processes. His work in logistics and device diagnostics complements these efforts by improving efficiency, safety, and reliability in manufacturing and energy systems. He is keenly interested in the intersection of Industry 4.0 and smart manufacturing, contributing to projects that integrate robotics, automation, and advanced digital technologies. These research interests demonstrate his vision of combining scientific discovery with practical applications to promote sustainable development and enhance global competitiveness in engineering and technological industries.

Research Skill

Prof. Dr. Saulius Baskutis possesses a comprehensive set of research skills that reflect his long-standing academic and industrial experience in engineering. He is highly skilled in experimental methods, particularly in the testing of materials, welding techniques, and coating technologies, where precision and innovation are essential. His ability to design, conduct, and analyze experiments has led to impactful findings published in internationally recognized journals. He demonstrates strong competencies in project management, having successfully led and contributed to national and international research initiatives, including EU-funded programs. His skills extend to collaborative research, working with multidisciplinary teams across Europe to address complex technological challenges. Additionally, he is adept in applying digital tools such as CAD, CAM, and CNC systems to align with Industry 4.0 practices. His ability to bridge theoretical knowledge with applied solutions highlights his strength as both a researcher and innovator, ensuring his contributions remain relevant and forward-looking.

Publications Top Notes

Title: Numerical Method for Internal Structure and Surface Evaluation in Coatings
Authors: Tomas Kačinskas, Saulius Baskutis
Year: 2025

Title: Modeling of Vibrational-Centrifugal Strengthening for Functional Surfaces of Machine Parts
Authors: Vadym Stupnytskyy, Yaroslav Kusyi, Egidijus Dragašius, Saulius Baskutis, Rafal Chatys
Year: 2024

Title: Investigation of the Properties of Anti-Friction Coatings Deposited with Different Casting Methods
Authors: Tomas Kačinskas, Saulius Baskutis, Jolanta Baskutienė, Lina Kavaliauskienė
Year: 2024

Title: Analytical Model of Tapered Thread Made by Turning from Different Machinability Workpieces
Authors: Oleh Onysko, Volodymyr Kopei, Cristian Barz, Yaroslav Kusyi, Saulius Baskutis, Michal Bembenek, Predrag Dašić, Vitalii Panchuk
Year: 2024

Title: Control of the Parameters of the Surface Layer of Steel Parts During Their Processing Applying the Material Homogeneity Criterion
Authors: Kusyi Yaroslav, Stupnytskyy Vadym, Kostiuk Olha, Oleh Onysko, Egidijus Dragašius, Saulius Baskutis, Rafał Chatys
Year: 2024

Title: Simulation and Analytical Studies of Chip Formation Processes in the Cutting Zone of Titanium Alloys
Authors: Vadym Stupnytskyy, Xianning She, Egidijus Dragašius, Saulius Baskutis, Oleh Prodanchuk
Year: 2023

Title: Pool Boiling of Ethanol on Copper Surfaces with Rectangular Microchannels
Authors: Robert Kaniowski, Robert Pastuszko, Egidijus Dragašius, Saulius Baskutis
Year: 2023

Title: Influence of Additives on the Mechanical Characteristics of Hardox 450 Steel Welds
Authors: Saulius Baskutis, Jolanta Baskutiene, Egidijus Dragašius, Lina Kavaliauskiene, Neringa Keršiene, Yaroslav Kusyi, Vadym Stupnytskyy
Year: 2023

Title: Modeling and Simulation of Machined Surface Layer Microgeometry Parameters
Authors: Vadym Stupnytskyy, Egidijus Dragašius, Saulius Baskutis, She Xianning
Year: 2022

Title: Agent-Based Modelling Approach for Autonomous Vehicle Influence on Countries’ Welfare
Authors: Saulius Baskutis, Valentas Gružauskas, Peter Leibl, Linas Obcarskas
Year: 2022

Title: Effect of Chemical Composition of Clay on Physical-Mechanical Properties of Clay Paving Blocks
Authors: Rolandas Avizovas, Saulius Baskutis, Valentinas Navickas, László Tamándl
Year: 2022

Title: Perspectives and Problems of Using Renewable Energy Sources and Implementation of Local “Green” Initiatives: A Regional Assessment
Authors: Saulius Baskutis, Jolanta Baskutiene, Valentinas Navickas, Yuriy Bilan, Wojciech Cieśliński
Year: 2021

Title: Mechanical Properties and Microstructure of Aluminium Alloy AW6082-T6 Joints Welded by Double-Sided MIG Process Before and After Aging
Authors: Saulius Baskutis
Year: 2019

Title: Monitoring of Welding Process Parameters in Gas Tungsten Arc Welding of Carbon Steel Weldments
Authors: Saulius Baskutis
Year: 2019

Title: Effect of Weld Parameters on Mechanical Properties and Tensile Behavior of Tungsten Inert Gas Welded AW6082-T6 Aluminium Alloy
Authors: Saulius Baskutis
Year: 2019

Title: Research on Mechanical Properties of TIG Welded Aluminum Alloy
Authors: Bendikiene R., Baskutis S., Baskutiene J., Ciuplys A.
Year: 2018

Title: Comparative Study of TIG Welded Commercially Pure Titanium
Authors: Saulius Baskutis
Year: 2018

Title: Minimizing the Trade-Off Between Sustainability and Cost Effective Performance by Using Autonomous Vehicles
Authors: Saulius Baskutis
Year: 2018

Title: The Analysis of Dissimilar Metal Weld Joints
Authors: Saulius Baskutis
Year: 2018

Title: Experimental Study of Welded Joints of Aluminium Alloy AW6082
Authors: Baskutis S., Baskutiene J., Bernotaitis E.
Year: 2017

Title: The Vibratory Alignment of the Parts in Robotic Assembly
Authors: Saulius Baskutis
Year: 2017

Title: Influence of Welding Modes on Weldability of Structural Steel Lap Joints in Laser Welding
Authors: Saulius Baskutis
Year: 2017

Title: Warehouses Consolidation in the Logistic Clusters: Food Industry’s Case
Authors: Saulius Baskutis
Year: 2016

Title: Nano and Microhardness Testing of Heterogeneous Structures
Authors: Saulius Baskutis
Year: 2016

Title: The Temperature Control Impact to the Food Supply Chain
Authors: Baskutis S., Navickas V., Gružauskas V., Olencevičiute D.
Year: 2015

Conclusion

Prof. Dr. Saulius Baskutis is highly deserving of the Best Researcher Award for his longstanding dedication to advancing engineering science, particularly in the fields of coatings, welding technologies, renewable energy, and sustainable manufacturing. His significant contributions through impactful publications, leadership in international research projects, and strong collaboration between academia and industry highlight his role in driving innovation and practical solutions for society. With his expertise, professional recognition, and commitment to mentoring future generations, he demonstrates both past excellence and strong potential for continued research leadership and global impact in the years ahead.

Puja Gupta | Computer Vision | Excellence in Research

Published on by Computer Vision Awards

Dr. Puja Gupta | Computer Vision | Excellence in Research

Asst Professor at Shri G.S. Institute of Technology & Science | India

Dr. Puja Gupta is a dedicated researcher and academic with expertise in artificial intelligence, machine learning, IoT, and smart computing technologies. She has contributed significantly to the field through her high-quality publications in reputed journals, patents, and innovative product development. Her work has addressed real-world challenges in healthcare, security, and sustainable technologies, bridging the gap between research and practical applications. With a strong academic foundation, she has successfully guided students in research and projects, fostering innovation and academic growth. She has been actively involved in international collaborations, research projects, and academic leadership roles, contributing to the advancement of her field. She is also a committed member of professional organizations, demonstrating her engagement in the broader research community. Her impactful contributions, leadership potential, and dedication to continuous professional development make her a valuable asset to both academia and society.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Puja Gupta holds a strong academic background in computer science and engineering, culminating in a doctoral degree specializing in artificial intelligence and smart systems. Her Ph.D. research focused on the integration of machine learning techniques and IoT frameworks to design intelligent solutions that address complex societal problems. Prior to her doctoral studies, she earned her master’s and bachelor’s degrees in computer science, gaining a solid foundation in algorithms, data structures, and system design. Throughout her academic journey, she demonstrated exceptional commitment to learning, consistently achieving top ranks and recognition for her research contributions. Her advanced education has equipped her with in-depth knowledge of computational intelligence, optimization techniques, and applied research methodologies, enabling her to contribute effectively to both theoretical advancements and practical applications in the field. Her academic background continues to support her innovative research and teaching excellence in the areas of AI, IoT, and emerging technologies.

Professional Experience

Dr. Puja Gupta has extensive professional experience in both academic and research domains, with a focus on artificial intelligence, IoT, and smart computing solutions. She has worked as a faculty member at prestigious institutions, where she has taught and mentored students at undergraduate and postgraduate levels, guiding them in research projects and fostering innovation. Alongside teaching, she has been actively involved in funded research projects, many of which involved international collaborations and multidisciplinary teams. She has successfully published her findings in reputed journals and conferences indexed in IEEE and Scopus, and her work has also resulted in patents and prototypes with practical applications. Beyond academia, she has contributed to the research community by serving as a reviewer, participating in editorial activities, and organizing academic events. Her leadership roles in academic programs and community-driven initiatives further highlight her commitment to advancing knowledge and supporting the development of future researchers.

Research Interest

Dr. Puja Gupta’s research interests revolve around artificial intelligence, machine learning, IoT, big data analytics, and smart system design. She is particularly focused on developing intelligent solutions that address pressing societal challenges in areas such as healthcare, security, and sustainability. Her work often integrates computational intelligence with real-world applications, such as predictive healthcare models, smart monitoring systems, and secure communication frameworks for IoT devices. She is also keen on advancing research in explainable AI and optimization algorithms to ensure reliability and transparency in machine learning systems. Another area of interest is the development of resource-efficient AI models for deployment in edge and cloud environments. Her multidisciplinary approach allows her to collaborate across domains, leveraging data-driven techniques to innovate practical solutions. By combining theoretical knowledge with applied research, she aims to contribute to technological advancements that enhance the quality of life and create sustainable, impactful outcomes for society.

Award and Honor

Dr. Puja Gupta has been recognized with numerous awards and honors that highlight her academic excellence, research contributions, and leadership in the field of computer science and engineering. Her achievements include recognition for publishing impactful research in reputed journals, presenting at leading international conferences, and securing patents that demonstrate the practical value of her work. She has also been honored for her contributions to student mentoring and academic program development, reflecting her dedication to nurturing young talent. Several of her awards acknowledge her innovative approaches in AI and IoT research, particularly for developing solutions with direct societal impact. In addition, she has received appreciation for her involvement in community-driven initiatives and leadership in professional organizations. These honors not only recognize her past accomplishments but also serve as a testament to her commitment, perseverance, and ability to inspire others in the academic and research communities.

Research Skill

Dr. Puja Gupta possesses advanced research skills in artificial intelligence, machine learning, IoT systems, and computational modeling, enabling her to conduct impactful and interdisciplinary research. She is proficient in applying data analysis techniques, optimization algorithms, and predictive modeling to design intelligent solutions for real-world applications. Her expertise includes working with various programming languages, simulation tools, and research frameworks that support scalable and innovative problem-solving. She has developed strong skills in experimental design, result validation, and research dissemination through high-quality publications and conference presentations. Beyond technical expertise, she excels in collaborative research, often working with international teams and multidisciplinary groups to drive innovation. She is also skilled in project management, proposal writing, and securing research funding, which have been instrumental in the successful execution of her projects. Her research skills, combined with her commitment to continuous learning, position her as a versatile and resourceful academic and researcher in her field.

Publications Top Notes

Title: Impact of knowledge management practices on innovative capacity: A study of telecommunication sector
Authors: J Jyoti, P Gupta, S Kotwal
Year: 2011
Citation: 56

Title: A Novel Algorithm for Mask Detection and Recognizing Actions of Human
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 48

Title: Transcriptional mechanisms underlying sensitization of peripheral sensory neurons by granulocyte-/granulocyte-macrophage colony stimulating factors
Authors: KK Bali, V Venkataramani, VP Satagopam, P Gupta, R Schneider, …
Year: 2013
Citation: 42

Title: Minimally invasive plate osteosynthesis (MIPO) for proximal and distal fractures of the tibia: a biological approach
Authors: P Gupta, A Tiwari, A Thora, JK Gandhi, VP Jog
Year: 2016
Citation: 41

Title: SUMOylation of enzymes and ion channels in sensory neurons protects against metabolic dysfunction, neuropathy, and sensory loss in diabetes
Authors: N Agarwal, FJ Taberner, DR Rojas, M Moroni, D Omberbasic, C Njoo, …
Year: 2020
Citation: 39

Title: An introduction of soft computing approach over hard computing
Authors: P Gupta, N Kulkarni
Year: 2013
Citation: 31

Title: People detection and counting using YOLOv3 and SSD models
Authors: P Gupta, V Sharma, S Varma
Year: 2021
Citation: 30

Title: Challenges in the adaptation of IoT technology
Authors: Neha, P Gupta, MA Alam
Year: 2021
Citation: 20

Title: Role of fine needle aspiration cytology in preoperative diagnosis of ameloblastoma
Authors: S Bisht, SA Kotwal, P Gupta, R Dawar
Year: 2009
Citation: 13

Title: Let the Blind See: An AIIoT based device for real-time object recognition with the voice conversion
Authors: P Gupta, M Shukla, N Arya, U Singh, K Mishra
Year: 2022
Citation: 9

Title: The impact of artificial intelligence on renewable energy systems
Authors: P Gupta, S Kumar, YB Singh, P Singh, SK Sharma, NK Rathore
Year: 2022
Citation: 8

Title: Simultaneous feature selection and clustering of micro-array and RNA-sequence gene expression data using multiobjective optimization
Authors: AK Alok, P Gupta, S Saha, V Sharma
Year: 2020
Citation: 8

Title: Activity detection and counting people using mask-RCNN with bidirectional ConvLSTM
Authors: P Gupta, U Singh, M Shukla
Year: 2022
Citation: 7

Title: Study of cloud providers (azure, amazon, and oracle) according to service availability and price
Authors: A Rajput, P Gupta, P Ghodeshwar, S Varma, KK Sharma, U Singh
Year: 2023
Citation: 6

Title: Machine learning approaches for IoT-data classification
Authors: O Farooq, P Gupta
Year: 2020
Citation: 5

Title: Evaluation of AI system’s voice recognition performance in social conversation
Authors: SK Barnwal, P Gupta
Year: 2022
Citation: 4

Title: Analysis of CNN Model with Traditional Approach and Cloud AI based Approach
Authors: U Kushwaha, P Gupta, S Airen, M Kuliha
Year: 2022
Citation: 4

Title: Analysis of crowd features based on deep learning
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 4

Title: Acknowledgment of patient in sense behaviors using bidirectional ConvLSTM
Authors: U Singh, P Gupta, M Shukla, V Sharma, S Varma, SK Sharma
Year: 2023
Citation: 3

Title: Study on the NB-IoT based smart medical system
Authors: P Gupta, AK Pandey
Year: 2023
Citation: 3

Conclusion

Dr. Puja Gupta is highly deserving of the Best Researcher Award for her significant contributions to advancing research in artificial intelligence, IoT, and smart technologies, as well as her role in mentoring students and fostering innovation. Her impactful work, including patents, high-quality publications, and practical product development, has addressed societal challenges in healthcare, security, and sustainability. With her strong academic background, leadership in academic and community initiatives, and commitment to continuous growth, she holds great potential to further excel in future research, expand global collaborations, and take on greater leadership roles in the academic and research community.

Jie Han | Image Deblurring | Best Researcher Award

Published on by Computer Vision Awards

Mr. Jie Han | Image Deblurring | Best Researcher Award

Lecturer at Nanjing University of Information Science and Technology | China

Mr. Jie Han is an academic researcher specializing in mathematical modeling, surveying engineering, and remote sensing image processing. His expertise lies in developing advanced algorithms for errors-in-variables models, optical image restoration, and ill-posed inversion problems. He has consistently contributed to high-impact publications in leading journals such as IEEE Transactions on Geoscience and Remote Sensing, Remote Sensing, and Information Sciences, which reflect his commitment to advancing knowledge and practice in his field. Dr. Han has participated in prominent international conferences, sharing his research and collaborating with peers from diverse backgrounds. As a lecturer at Nanjing University of Information Science and Technology, he combines teaching with active research, mentoring young scholars, and fostering innovation. His scholarly contributions have not only enhanced theoretical approaches but also supported practical applications in geoinformatics and environmental monitoring. With an expanding academic portfolio, Dr. Han continues to establish himself as a promising researcher with international impact.

Professional Profile 

ORCID Profile 

Education

Mr. Jie Han has pursued an extensive academic journey in the fields of surveying engineering, geoinformatics, and remote sensing. He began his undergraduate studies in Surveying and Mapping Engineering at Hefei University of Technology, where he gained a solid foundation in geospatial sciences, cartography, and mathematical modeling. He later continued his academic career by pursuing doctoral studies at Tongji University in Shanghai, one of China’s leading institutions in engineering and geoscience research. There, he specialized in surveying and geoinformatics, focusing on errors-in-variables models and advanced statistical approaches for solving ill-posed problems. His doctoral research contributed significantly to advancements in precision estimation, image restoration, and hyperspectral data analysis. Following his doctoral degree, he transitioned into academia as a lecturer at the School of Mathematics and Statistics at Nanjing University of Information Science and Technology. His educational background combines rigorous training in engineering and mathematics, which serves as the basis for his diverse research contributions.

Professional Experience

Mr. Jie Han has developed his professional career through a balanced combination of teaching, research, and scholarly collaboration. He currently serves as a lecturer at the School of Mathematics and Statistics at Nanjing University of Information Science and Technology, where he contributes to both undergraduate and graduate-level education while supervising research activities. In his role, he integrates theoretical knowledge with practical research applications, fostering academic growth among students and peers. Prior to this appointment, his professional experience was shaped by his doctoral training at Tongji University, where he engaged in several collaborative projects in surveying, image processing, and statistical modeling. He has also actively participated in international conferences such as IEEE IGARSS and ISPRS, presenting his research and establishing academic connections worldwide. His professional journey reflects a consistent dedication to advancing geoinformatics and remote sensing applications while contributing to the global academic community through research dissemination and academic service.

Research Interest

Mr. Jie Han’s research interests lie at the intersection of mathematical modeling, geoinformatics, and remote sensing image analysis. A central area of his work focuses on errors-in-variables models, where he explores improved estimation methods for solving statistical and mathematical challenges in measurement and modeling. He is also deeply engaged in the development of algorithms for optical image restoration, including image denoising, deblurring, and dehazing, which have direct applications in enhancing the quality and usability of remote sensing data. His research extends to ill-posed inversion problems, where he investigates solutions for complex data reconstruction in radar and hyperspectral imaging. Beyond theory, Dr. Han is interested in practical applications such as environmental monitoring, image-based mapping, and atmospheric studies. By combining statistical analysis with computational techniques, his research bridges theoretical foundations with real-world challenges, contributing to advancements in geospatial sciences, remote sensing technologies, and interdisciplinary applications across scientific and engineering domains.

Award and Honor

Mr. Jie Han has been recognized for his academic achievements through his publications in highly reputed journals and his participation in international conferences that highlight the significance of his contributions. The acceptance of his work in leading journals such as IEEE Transactions on Geoscience and Remote Sensing, Remote Sensing, and Information Sciences serves as a mark of distinction, as these platforms are highly competitive and widely respected in the scientific world. Additionally, his role as first and corresponding author in multiple publications showcases his leadership and initiative in research. His invited participation in academic gatherings such as IEEE IGARSS and ISPRS further highlights his growing visibility in the global scientific arena. With continued engagement and expansion of his research influence, future recognitions and awards are strongly anticipated.

Research Skill

Mr. Jie Han possesses a wide range of research skills that combine mathematical expertise with computational and applied techniques. He is proficient in designing and applying errors-in-variables models for statistical estimation problems, offering innovative methods for handling uncertainty in measurements. His skills in optical image processing include advanced methods for denoising, deblurring, and dehazing, which significantly improve the quality of remote sensing data. He is also experienced in addressing ill-posed inversion problems using sparse regularization and tensor-based techniques, which are essential for solving complex imaging challenges. His technical competence extends to hyperspectral image analysis, radar imaging, and environmental data modeling. In addition, he has strong analytical and programming skills, enabling the development of algorithms and models that bridge theory with real-world applications. His experience in writing and publishing high-quality research papers also demonstrates his ability to communicate complex concepts effectively, making his skills both versatile and impactful in the scientific community.

Publications Top Notes

Title: Novel Regularization Method of Adaptively Balanced L1 and L2 Norms with Bias Removal
Authors: Jie Han; Zhichao Zhang; Shouzhu Zheng; Qing Fu; Wenping Song; Haiyong Ding; Minghua Wang; Weiguo Huang
Year: 2025

Title: Comparison of Posterior Precision Estimation Methods of Weighted Total Least-Squares Solution for Errors-in-Variables Model
Authors: Jie Han; Songlin Zhang; Shimeng Dong; Qingyun Yan
Year: 2024

Title: A Nonblind Deconvolution Method by Bias Correction for Inaccurate Blur Kernel Estimation in Image Deblurring
Authors: Jie Han; Songlin Zhang; Zhen Ye
Year: 2023

Title: Double-Factor Tensor Cascaded-Rank Decomposition for Hyperspectral Image Denoising
Authors: Jie Han; Chuang Pan; Haiyong Ding; Zhichao Zhang
Year: 2023

Title: Automatic Registration of Very Low Overlapping Array InSAR Point Clouds in Urban Scenes
Authors: Xiaohua Tong; Xin Zhang; Shijie Liu; Zhen Ye; Yongjiu Feng; Huan Xie; Longyong Chen; Fubo Zhang; Jie Han; Yanmin Jin et al.
Year: 2022

Title: Bias Analysis and Correction for Ill-Posed Inversion Problem with Sparsity Regularization Based on L1 Norm for Azimuth Super-Resolution of Radar Forward-Looking Imaging
Authors: Jie Han; Songlin Zhang; Shouzhu Zheng; Minghua Wang; Haiyong Ding; Qingyun Yan
Year: 2022

Title: Local Patchwise Minimal and Maximal Values Prior for Single Optical Remote Sensing Image Dehazing
Authors: Jie Han
Year: 2022

Title: Spatiotemporal PM2.5 Estimations in China from 2015 to 2020 Using an Improved Gradient Boosting Decision Tree
Authors: Weihuan He; Huan Meng; Jie Han; Gaohui Zhou; Hui Zheng; Songlin Zhang
Year: 2022

Title: Closure to “New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model”
Authors: Jie Han; Songlin Zhang; Jingchang Li
Year: 2022

Title: Indoor Map Boundary Correction Based on Normalized Total Least Squares of Condition Equation
Authors: Jie Han
Year: 2021

Title: Quality Evaluation of Linear Inequality Constrained Estimation by Monte Carlo Sampling in Parameter Space
Authors: Songlin Zhang; Jingchang Li; Kun Zhang; Jie Han
Year: 2021

Title: New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model
Authors: Jie Han; Songlin Zhang; Jingchang Li
Year: 2021

Title: A General Partial Errors-in-Variables Model and a Corresponding Weighted Total Least-Squares Algorithm
Authors: Jie Han; Songlin Zhang; Yali Li; Xin Zhang
Year: 2020

Conclusion

Mr. Jie Han is a deserving candidate for the Best Researcher Award as he has made significant contributions in mathematical modeling, remote sensing, and optical image restoration through innovative methods and high-quality publications in reputed journals and conferences. His research has advanced both theoretical foundations and practical applications, contributing to progress in geoinformatics and environmental monitoring. With his strong academic background, consistent research output, and growing recognition in the scientific community, he shows great potential for future leadership, expanded collaborations, and impactful contributions to global scientific and societal challenges.