Marina Ivasic-Kos | computer vision | Research and Innovation Citation Excellence Award

Prof Dr. Marina Ivasic-Kos, computer vision, Research and Innovation Citation Excellence Award

Professor  at the University of Rijeka, Croatia

Dr. Marina Ivašić-Kos is a renowned computer scientist and professor at the University of Rijeka, Croatia. With expertise in computer vision and deep learning, she specializes in applications such as person detection in search and rescue, thermal object detection, and activity-based player recognition. Dr. Ivašić-Kos has led various research projects, published extensively in reputable journals, and holds key positions in academic committees. Her impactful contributions include innovative models for image annotation, showcasing a multi-faceted approach integrating machine learning and fuzzy-knowledge representation schemes. As a distinguished figure in the field, she continues to advance the frontiers of intelligent systems and pattern analysis.

Professional Profiles:

Scopus Profile

Orcid Profile

GoogleScholar profile

Researchgate profile

LinkedIn profile

📚 Education:

Ph.D. degree in Computer Science (2002-2012): Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb M.Sc. degree in Information Science (1997-2001): Faculty of Philosophy, University of Zagreb, Department of Information Science, Zagreb.

Work Experience:

Present Employer: Faculty of Informatics and Digital Technologies, University of Rijeka, and Centre for Artificial Intelligence and Cybersecurity, University of Rijeka Position: Professor Head of Laboratory for Pattern Recognition and Soft Computing Head of Laboratory for Computer Vision, Virtual and Augmented Reality at the Centre for Artificial Intelligence, University of Rijeka Responsibilities: Teaching on postgraduate, graduate, and Doctoral Studies in various subjects Project leader and researcher in computer vision scientific projects President of the Publishing Committee at the Department of Informatics Member of various university councils and committees.

Training:

Year 22.-26.7.2019: Place of training: Warsaw, Poland Training on Deep Learning by IRDTA Brussels, London Year 4.-6. 9.2017: Place of training: Ionic Center, Athens, Greece Training on Integration in Cognitive Robotics by IV&L Net Training School Year 2016: Place of training: Las Palmas De Gran Canaria, Spain Training on Biometry and de-identification by COST IC1206 2nd Training School Year 21.-24. 3. 2016: Place of training: University of Malta, Msida, Malta Training on Computer Vision and Deep Learning by The 2nd iV&L Net Summer School.

Technical skills and competencie

Computer vision, machine and deep learning, recognition and detection of objects, recognition of actions (Matlab, Keras, TesorFlow) – fuzzy systems, knowledge representation – programming, work on developing and implementing applications (Java, C++, Oracle) – design of IS projects (Agile, Scrum, UML).

Research Focus

Dr. Marina Ivašić-Kos specializes in the research areas of computer vision, image processing, and pattern analysis. Her work encompasses the development and application of deep learning techniques, particularly Convolutional Neural Networks (CNN), for tasks such as automatic person detection in search and rescue operations. Additionally, she has expertise in thermal object detection under challenging weather conditions using YOLO, and active player detection in handball scenes based on activity measures. Dr. Ivašić-Kos has contributed significantly to the field of image annotation, proposing innovative models such as a two-tier image annotation model with a multi-label classifier and fuzzy-knowledge representation scheme. Her research also extends to knowledge-based multi-layered image annotation systems, Bayesian classifiers, and fuzzy Petri net knowledge representation schemes.

Publications (TOP NOTES):

 

Deep Learning Approach for Objects Detection in Underwater Pipeline Images, Cited by 12, Publication date: 2022/12/31.

 

Review and analysis of synthetic dataset generation methods and techniques for application in computer vision, Cited by 12, Publication date: 2023/1/30.

 

Thermal object detection in difficult weather conditions using YOLO, Cited by 197, Publication date: 2020/7/6.

 

Automatic person detection in search and rescue operations using deep CNN detectors, Cited by 93, Publication date: 2021/3/4.

 

An overview of Human Action Recognition in sports based on Computer Vision, Cited by 41, Publication date: 2022/6/1.

 

A new approach to dominant motion pattern recognition at the macroscopic crowd level, Cited by 31, Publication date: 2022/11/1.

 

Person Detection in thermal videos using YOLO, Cited by 25, Publication date: 2020

 

Tracking Handball Players with the DeepSORT Algorithm.,Cited by 24, Publication date: 2020/2.

 

Active player detection in handball scenes based on activity measures,. Cited by 22, Publication date: 2020/3/8

 

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Sujatha Moorthy | Artificial Intelligence | Most Cited Article Award

Dr. Sujatha Moorthy | Artificial Intelligence | Most Cited Article Award

PHD at Sathyabama University, India

🌦️📚  Dr. M. Sujatha is a seasoned professional with 22 years of experience, specializing in Wireless Sensor Networks and RF Antenna technology. Holding a Ph.D. from Sathyabama University, Chennai, her research focuses on developing and validating antenna models to enhance the efficiency of wireless sensor applications. As a Professor at KL University, Vijayawada, she has contributed significantly to academia, with numerous publications in reputable international journals. Driven by a passion for innovation, she is actively involved in cutting-edge projects, showcasing her expertise in machine learning, robotics, and high-resolution satellite remote sensing. A dedicated scholar, she continues to shape the future of technology. 🌍

Professional Profiles:

Orcid profile

googlescholar profile

Researchgate profile

LinkedIn

 

🎓Education:

💼 Ph.D., Sathyabama University, Chennai (July 2017) Faculty of Electronics Engineering, Highly Recommended M.E., Sathyabama University, Chennai (May 2006) Applied Electronics, I Class with Distinction B.E., Adhiparasakthi Engg. College, Madras University (May 1999) Electronics and Communication Engineering, I Class  🌍👩‍🔬

Professional Experience:

Total 22 years of experience, with 16 years post M.E. Professor, KL University, Vijayawada, Andra Pradesh (December 2020-Till date) Professor, Saveetha School of Engineering, SIMATS (April 2019-December 2020) Professor, KL University, Vijayawada, Andra Pradesh (January 2017-March 2019) Associate Professor, Prathyusha Institute of Technology and Management (December 2003 – June 2016) Lecturer, Sri Ram Engineering College (June 2000-December 2003)

Professional Qualification:

FPGA Based Industrial Robotic Arm Controller, Design Engineering (Toronto), ISSN: 0011-9342 | Year 2022, Issue: 1, Pages: 2209 – 2215. Maze Solver Using Webots, Design Engineering (Toronto), ISSN: 0011-9342 Year 2022, Issue: 1, Pages: 2563 – 2568.

Research Focus:

Dr. M. Sujatha’s research spans varmetamaterialsious domains, primarily focusing on Wireless Sensor Networks (WSN), RF Antennas, and their applications in cutting-edge technologies. Her work includes the development of high-performance grouping schemes for WSN, innovative antenna designs inspired by metamaterials, and hardware design for biomedical video compression. Additionally, she explores AI-based traffic flow prediction models for connected and autonomous electric vehicles. Dr. Sujatha’s research extends to biometric voting systems, electronic voting machines, and the detection of fake news, showcasing a diverse expertise in wireless communication, IoT applications, and information security. Her multidisciplinary contributions demonstrate a holistic approach to technological advancements.⚡🔬

Peer Reviewer & Academic Engagements:

Dr. M. Sujatha, citation metrics and indices from Google Scholar are as follows:

Citations: 115 (All), 93 (Since 2018)
h-index: 6 (All), 6 (Since 2018)
i10-index: 4 (All), 3 (Since 2018)

Publications (TOP NOTES)

 

Metamaterial Inspired Circular Antenna with DGS for Tetra Band Application, cited by 8, publication date: 2020/3/25

 

AI Based Traffic Flow Prediction Model for Connected and Autonomous Electric Vehicles, cited by 7, publication date: 2021/11.

 

AR-ESIHE and ARS-ESIHE-based image enhancement methods on 9oba pure and nano dispersed liquid crystalline compound, cited by 5, publication date: 2020/8

 

Design of Reconfigurable Integrated patch antenna in ISM band for IoT applications, cited by 5, publication date: 2020/7/23

 

Unconstrained Global Optimization Base Partial Transmit Sequence for OFDM PAPR Reduction, cited by 4, publication date: 2020/4/15.

 

Image enhancement using wavelet based image fusion and power law transform, cited by 2, publication date: 2020/5/15

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