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Real-time tracking of fast-moving object in occlusion scene

Journal of systems Engineering and Electronics 2024年第3期35卷 741-752页

作者： LI Yuran LI Yichen ZHANG Monan YU Wenbin GUAN Xinping Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Systems Control and Information Processing Ministry of Education of ChinaShanghai 200240China

Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.

关键词： speed-accuracy balanced motion modeling constrained updater

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Expert algorithm to optimize the process of selecting a topic for a research project with the assistance of ChatGPT 6

Expert algorithm to optimize the process of selecting a topi...

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6th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Rashidov, Aldeniz Department of Automation information and control systems Technical University of Gabrovo Gabrovo Bulgaria

ISBN: (纸本)9798350394634

This paper presents the development of an expert algorithm aimed at optimizing the process of selecting a topic for a research project by integrating ChatGPT capabilities with research expertise. The algorithm aims to support researchers and scientists by providing a structured approach to select relevant and appropriate research topics based on current trends in the field, the interests and capabilities of the research team. The research reveals the potential of AI to significantly improve the efficiency and quality of scientific processes by rapidly analyzing huge data sets and providing personalized recommendations that are aligned with team goals. The work highlights the importance of continuously embedding innovation in academia to ensure meaningful advances and quality research in the future. © 2024 IEEE.

关键词： Decision making

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An Algorithm to Support the Review Process of a Scientific Research Project Proposal Using ChatGPT 8

An Algorithm to Support the Review Process of a Scientific R...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Rashidov, Aldeniz Department of Automation information and control systems Technical University of Gabrovo Gabrovo Bulgaria

ISBN: (纸本)9798350354423

Reviewing scientific research project proposals (SRPPs) is essential for the development of scientific knowledge and innovation. Traditional peer review methods often face challenges such as significant drafting time, subjective evaluations, and a shortage of qualified reviewers, which reduce the quality of reviews. With the development of artificial intelligence, the potential for improving the peer review process is being discovered. This study proposes and evaluates an algorithm to assist the peer review process using ChatGPT. The algorithm aims to optimize the review process by automating the analysis, generating objective scores using weighting coefficients, SWOT analysis and providing feedback on various aspects of project proposals. The study analyses the effectiveness of the algorithm through a SWOT analysis that highlights its strengths, weaknesses, opportunities and threats. The algorithm may be useful for reviewers, researchers and academic institutions seeking to enhance the effectiveness and objectivity of SRPP evaluation. © 2024 IEEE.

关键词： Algorithm Artificial Intelligence ChatGPT Evaluation Project Review SWOT Analysis

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Automating Citation Formatting in Scientific Publications Using ChatGPT 1

Automating Citation Formatting in Scientific Publications Us...

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1st Asian Conference on Communication and Networks, ASIANComNet 2024

作者： Rashidov, Aldeniz Technical University of Gabrovo Department of Automation Information and Control Systems Gabrovo Bulgaria

ISBN: (纸本)9798350367003

In academic writing, the accuracy of citation formatting in scientific publications is essential for maintaining the integrity and consistency of scientific communication. However, manually formatting citations according to different styles, such as the IEEE, APA, or MLA, can be time-consuming and error-prone. This paper presents an innovative approach to automate citation formatting in scientific publications using ChatGPT. It proposes an algorithm that incorporates a sequence of instructions and guidance, combined with the capabilities of ChatGPT, and greatly simplifies the process of formatting citations according to different styles. The proposed approach involves training ChatGPT with a dataset containing citation guides and examples from different formatting styles to improve its ability to generate correctly formatted citations. This work presents a comparative characterization of the existing automated citation formatting systems and the proposed algorithm with ChatGPT. Their functionalities are analyzed and their advantages and disadvantages are highlighted. In addition, a SWOT analysis of the systems is performed, which examines their strengths, weaknesses, opportunities, and threats. The analysis highlights the effectiveness and advantages of the proposed solution with ChatGPT. The results show that automation using ChatGPT not only facilitates accurate citation formatting but also offers a practical tool for improving the quality and relevance of scientific publications. ChatGPT can significantly reduce formatting errors and improve the efficiency of academic writing, offering a scalable solution for researchers and institutions. © 2024 IEEE.

关键词： automation

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Algorithm for generating an abstract of a scientific publication with the assistance of ChatGPT 15

Algorithm for generating an abstract of a scientific publica...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rashidov, Aldeniz Technical University of Gabrovo Department of Automation information and control systems Gabrovo Bulgaria

ISBN: (纸本)9798350370249

This work presents the development of an algorithm for automated abstract generation of scientific publications that integrates the capabilities of ChatGPT with expertise in the field of academic writing. The development of such an algorithm is essential for optimizing abstract creation processes, especially for complex topics or high quality requirements. The algorithm allows customization of abstracts according to authors' specific needs. It includes functionalities for evaluation of the generated response, SWOT analysis of abstract structure and content, translation of the text into different languages, and grammar and spell checking, thus providing a means to produce quality abstracts in accordance with academic standards. The study highlights the role of artificial intelligence as an indispensable tool in scientific research, emphasizing the importance of continuously applying technological innovation to ensure meaningful scientific advances. © 2024 IEEE.

关键词： Abstract creation Academic research Academic writing Expert algorithm Research optimization

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A mathematical model for optimal scheduling of classes in a higher education institution 15

A mathematical model for optimal scheduling of classes in a ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rashidova, Fatme Rashidov, Aldeniz Technical University of Gabrovo Department of Automation Information and Control Systems Gabrovo Bulgaria

ISBN: (纸本)9798350370249

Timetabling is essential for the organization and functioning of higher education institutions (HEIs). This complex task requires balancing various factors such as availability of teachers, availability of halls, huge number of students in each specialty and course, preferences and satisfaction of students and teachers (agents). Although it may seem like a routine administrative activity, the compilation of a timetabling is indeed a multi-criteria task and requires the use of algorithms and optimization methods. The aim of the timetabling is to ensure the optimal distribution of learning activities in time and space, ensuring efficient use of resources, priorities and meeting the needs of all participants in the learning process, namely the agents. A properly designed timetabling not only contributes to improving the academic success of the students but also facilitates the work of the teachers and administration of the university. In this context, the development of mathematical models and computer systems for the automated compilation of timetabling is crucial for the modern management of the educational process. These tools not only optimize the process of composing timetabling, but also provide opportunities for adaptation to changing needs and conditions in HEIs. © 2024 IEEE.

关键词： Students

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WDCLF method for Web database design

WDCLF method for Web database design

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2024 IEEE International Conference on Computing, ICOCO 2024

作者： Rashidov, Aldeniz Department of Automation information and control systems Technical University of Gabrovo Gabrovo Bulgaria

ISBN: (纸本)9798331530303

This paper presents the WDCLF (Web Declare, Conceptual, Logical, Physical) method for web database design (WDB), which has been adapted to the needs of web applications. The WDCLF extends traditional database design approaches by adding specific elements related to Web-based systems. WDCLF offers a multi-layered architecture that allows parallel development of the data model and the processing model, accelerating the design and implementation processes. The method ensures high coordination between teams, which helps to flexibly adapt to changing requirements. Key benefits of WDCLF include scalability, security and optimized performance - key factors for the efficient operation of modern web applications. WDCLF enables integration with external systems, ensuring stability and performance under load. ©2024 IEEE.

关键词： Web Design

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SWOT analysis of distance learning for engineering students and strategies to improve the quality of learning 15

SWOT analysis of distance learning for engineering students ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rashidova, Fatme Technical University of Gabrovo Department of Automation Information and Control Systems Gabrovo Bulgaria

ISBN: (纸本)9798350370249

Unlike teaching theoretical subjects, teaching practical subjects have differences and require some special considerations. In a higher education institution (HEI) with a technical focus, learning practical skills is most often associated with seminars and laboratory exercises, specialized materials and equipment, smaller learner group sizes, and often longer blocks of time (a discipline's instructional hour) for practical training. In distance learning (DL), teaching practical skills poses significantly more difficulties than teaching theory. The purpose of this paper is to present a SWOT analysis for DL of engineering students. With the help of this analysis, decisions can be made to improve the quality of distance education. This SWOT analysis presents some of the main aspects of DL for engineering specialties in HEIs and can serve as a starting point for a more detailed study of the situation encountered in DL. © 2024 IEEE.

关键词： Contrastive Learning

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Challenges and limitations in the use of artificial intelligence in research and some options to overcome them 15

Challenges and limitations in the use of artificial intellig...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rashidov, Aldeniz Rashidova, Fatme Technical University of Gabrovo Department of Automation information and control systems Gabrovo Bulgaria

ISBN: (纸本)9798350370249

Artificial intelligence (AI) is becoming increasingly important in the field of scientific research, providing new opportunities for processing large amounts of data, automating routine tasks, and discovering new dependencies in complex systems. Despite these advantages, the use of AI in the scientific domain is accompanied by many challenges and limitations. This paper explores the current state of the problem, analyses the challenges facing the scientific community and examines the main limitations of using AI. The report includes a SWOT analysis of the deployment of AI in scientific research, summarizing the strengths, weaknesses, opportunities and threats that accompany the use of AI technologies. Possible solutions to overcome these limitations are proposed, including the development of new methodologies for AI training, the creation of ethical and legal frameworks, and the training of professionals who can effectively use AI technologies. The report highlights the need for a coordinated effort between the scientific community, industry and regulators for the successful application of AI in research. AI has the potential to significantly improve the scientific process, but requires careful management of the challenges and risks associated with its use. © 2024 IEEE.

关键词： AI Challenges AI Limitations Artificial Intelligence Ethical Issues Scientific Research

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SWOT Analysis of Online Examination of Engineering Students and Strategies to Improve Its Quality 8

SWOT Analysis of Online Examination of Engineering Students ...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Rashidova, Fatme Technical University of Gabrovo Department of Automation information and control systems Gabrovo Bulgaria

ISBN: (纸本)9798350354423

Online examination of engineering students is a complex and multi-layered process that requires careful planning and integration of various technologies. Engineering disciplines are characterized by high demands on students' practical skills and technical knowledge, making the online format particularly challenging. Online exams offer several advantages, including flexibility and accessibility, but also present challenges related to ensuring academic integrity and preventing cheating. To address these issues, teachers can use a variety of tools and strategies, including software solutions., time limits., and video monitoring of students during the exam. Effective student assessment is essential to measure success rates., identify strengths and weaknesses in the process., and adjust instruction to meet individual student needs. There are many different types of assessments that can be used., including interim assessments., summative assessments., and performance assessments. Overall., it is critical to take a balanced approach to online exams and student assessments., considering the strengths and challenges of these tools and ensuring that they are used in a fair and effective manner. By using effective tools and strategies., and promoting academic integrity., teachers can ensure that online exams are a valuable and reliable measure of student learning and progress. © 2024 IEEE.

关键词： Students

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