Rajesh Natarajan | Face Sketch Synthesis | Best Researcher Award

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Rajesh Natarajan | Face Sketch Synthesis | Best Researcher Award

Dr Rajesh Natarajan University of Technology and Applied Sciences-Shinas, Oman

Rajesh N completed his Ph.D. in Computer Science from Bharathiar University, Master of Computer Application from Thiruvalluvar University and BSc Computer science from Madras University. He is currently working as a Lecturer at University of Technology and Applied Sciences-Shinas, Sultanate of Oman. His research interest includes Data Mining, Machine Learning, Big Data Analytics, Blockchain Technology, and Data Privacy and Security. He has presented articles in the National and International conferences also published articles in reputed indexed journals like SCI, WoS and SCOPUS.

Education:

He earned his Doctor of Philosophy in Computer Science from Bharathiar University in Coimbatore, Tamil Nadu, India, in 2020. Prior to that, he completed his Master of Computer Application degree at Thiruvalluvar University in Vellore, Tamil Nadu, India, in 2008. His academic journey began with a Bachelor of Computer Science degree from Madras University in Chennai, Tamil Nadu, India, in 2005. Throughout his educational career, he has demonstrated a keen interest and dedication to the field of computer science. With a solid foundation established through his bachelor’s degree, he pursued advanced studies, culminating in a master’s degree that provided him with comprehensive knowledge and skills in computer applications. His pursuit of a Ph.D. reflects his commitment to scholarly research and his desire to contribute to the advancement of knowledge in the field. Through his academic achievements and professional experiences, he has developed a deep understanding of computer science concepts and their practical applications. He continues to leverage his expertise to make meaningful contributions to both academia and the broader technology industry.

Profile:

Experience:

He has an extensive academic background, having served as a Lecturer in the Department of Information Technology at the University of Technology and Applied Science in Shinas, Sultanate of Oman, since October 14, 2014. Prior to this role, he held the position of Assistant Professor in the Department of Computer Application at Sir M. Visvesvaraya Institute of Technology in Bangalore, India, from February 2, 2009, to October 11, 2014. With over a decade of experience in academia, he has demonstrated a strong commitment to excellence in teaching and research. Throughout his career, he has been dedicated to fostering a dynamic and engaging learning environment for his students, empowering them with the knowledge and skills necessary to succeed in the field of information technology. His tenure as both a Lecturer and Assistant Professor underscores his passion for education and his ability to inspire and mentor the next generation of IT professionals. Through his teaching, research, and leadership, he continues to make significant contributions to the academic community, shaping the future of technology education.

Publications:

  1. Blended ensemble learning prediction model for strengthening diagnosis and treatment of chronic diabetes disease Cited By : 42, Published By : 2022
  2. A Novel Framework on Security and Energy Enhancement Based on Internet of Medical Things for Healthcare 5.0 Cited By : 38, Published By : 2023
  3. Paddy plant disease recognition, risk analysis, and classification using deep convolution neuro-fuzzy network Cited By : 33, Published By : 2022
  4. Modified Self-Adaptive Bayesian algorithm for smart heart disease prediction in IoT system Cited By : 29, Published By : 2022
  5. Survey on privacy preserving data mining techniques using recent algorithms Cited By : 29, Published By : 2016
  6. A comparative performance analysis of machine learning approaches for the early prediction of diabetes disease Cited By : 19, Published By : 2022
  7. Association rules and deep learning for cryptographic algorithm in privacy preserving data mining Cited By : 17, Published By : 2019
  8. Survey on Malicious URL Detection Techniques Cited By : 12, Published By : 2022
  9. Secure Modern Wireless Communication Network Based on Blockchain Technology Cited By : 9, Published By : 2023
  10. Blinder Oaxaca and Wilk Neutrosophic Fuzzy Set-based IoT Sensor Communication for Remote Healthcare Analysis Cited By : 9, Published By : 2022

Xin Qian | Medical image application

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Mr. Xin Qian : Leading Researcher in Medical image application.

Chongqing University of Science and Technology, China.

Congratulations, Mr. Xin Qian, on winning the esteemed Excellence in Medical image application  Award from ResearchW! Your dedication, innovative research, and scholarly contributions have truly made a significant impact in your field. Your commitment to advancing knowledge and pushing the boundaries of research is commendable. Here’s to your continued success in shaping the future of academia and making invaluable contributions to your field. Well done!

Profile: Orcid

Education:
  • Jinggangshan University Network Engineering (Bachelor of Engineering)
  • Chongqing University of Science and Technology Safety Engineering (Artificial Intelligence) (Master of Engineering)
Internship Experience
  • 2020-04 ~ 2020-07 Hunan Zhongke Information Technology Research Institute Research assistant
  • 2021-09 ~ 2022-06 Chongqing University of Science and Technology Postgraduate research assistant
  • 2022-09 ~ 2023-09 Graphics, Image and Data Analysis Research Laboratory, Chongqing University of Science and Technology Deep Learning Lead for Horizontal Projects
Personal Achievements
  • At present, he has published 4 journal papers
  • 1 SCI paper in the first district (one student + corresponding author)
  • 3 Chinese papers (1 first author +2 top three)
  • 6 SCI papers in review: among them
  • 1 student + corresponding author is reviewing 2 SCI papers (Region III)
  • 1 SCI paper is reviewing SCI papers as the first author (Region III)
  • 3 SCI papers are participating in the review (Region III)
  • Representative SCI papers (4 papers in total, supervisor: Professor Han Qi, Professor Zhang Ao, Professor Feng Liping, * as corresponding author)
  • And 4 invention patents and 1 software copyright

Publications:

  1.  Qi Han, Xin Qian∗, Hongxiang Xua, Kepeng Wu, Lun Menga, Zicheng Qiu, Tengfei Weng. DM-CNN: Dynamic Multi-scale Convolutional Neural Networks with Uncertainty Quantification for Medical Image Classification [J]. Computers in Biology and Medicine, 2023；(SCI- Accepted， IF：7.7； JCR Q1)
  2.  Xin Qian, Tengfei Weng*, Chen Wu, HongXiang Xu, Yuan Tian, Mingyang Hou,T Zicheng Qiu,. SPCB-Net: A multi-scale skin cancer image identification network using self-interactive attention pyramid and cross-layer bilinear-trilinear pooling [J]. IEEE ACCESS, 2023；(SCI- Under review，IF：3.9； JCR Q1)
  3.  Liping Feng, Xin Qian∗, Ziyi Pei, Tengfei Weng, Qi Han, Zicheng Qiu, Yuan Tian, Guanzhong Liang, Guoyan Meng and Yaojun Hao. A Multi-View Ensemble-Based Weakly Supervised Model for Skin Lesion Images Diagnosis in Dermoscopic Images [J]. Electronics,2023.(SCI- Under review，IF：2.9； JCR Q2)
  4.  Ao Zhang, Xin Qian∗, Chengcheng Xu, Jie Zhang. A Novel Artificial-Intelligence-Based Approach for Automatic Assessment of Retinal Disease Images using Multi-view Deep-Broad Learning Network[J]. IEEE ACCESS, 2023.(SCI- Under review， JCR Q1)

Invention patents :

  1. Medical image classification method based on feature fusion and attention mechanism; Han Qi, Qian Xin, WENG Tengfei, XU Hongxiang et al. (Acceptance and disclosure)
  2. Detection method of UAV high-altitude shooting image based on dynamic convolutional neural network; Tian Yuan, AO Zhenyu, Qian Xin, Fu Wenlong et al. (Acceptance and disclosure)
  3. Small target detection method of tiny lymph node image based on attention mechanism; Han Qi, XU Hongxiang, Qian Xin, PEI Yangjun et al. (Acceptance and disclosure) 4）
  4. Steel defect image segmentation method based on introducing frequency domain deep learning network; Tian Yuan, FU Wenlong, WU Kepeng, Qian Xin et al. (Acceptance and disclosure)

Software copyright:

  1.  Kangaroo shelf shopping software v1.0, Qian Xin. Registration number: 2020SR078073

 

May your efforts cultivate a future where the skies are not only filled with innovation but are also fortified against the challenges that technological progress may bring.

Wishing you continued success in your endeavors to secure the future of Medical image application and computer aided medical diagnosis.

Warm Regards,
Award Manager,
Cybersecurity Awards,
International Research Awards on Cybersecurity and Cryptography,
cybersecurity@researchw.com