Dr. Johan Edstedt

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Biography

Johan Edstedt is a PhD student at Linköping University, focused on advancing methodologies in 3D reconstruction and computer vision. His notable publications include work on collaborative structure-from-motion techniques and advanced keypoint detection approaches. His research emphasizes the application of reinforcement learning to improve the accuracy and reliability of computer vision systems. Johan has contributed to several important conference proceedings, showcasing his innovative research on point cloud registration and classification. In the realm of academic publishing, he is involved in projects that enhance the understanding and application of machine learning in visual data processing.

Research Interests

Experience

PhD Student

— Present

Linköping University • Linköping, Sweden

Engaged in research and development in the fields of computer vision and 3D reconstruction methods.

Requirements for Linköping University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:5.5
Reading
Required:5.5
Writing
Required:5.5
Speaking
Required:5.5
Overall
Required:6.5
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:90
Prerequisites
Bachelor's degree with a major relevant to the program At least 30 ECTS credits in mathematics/applied mathematics and/or application of mathematics
Application Checklist
  • Certificates and diplomas from previous university studies
  • Transcript of records
  • Proof of English proficiency
  • Copy of passport/ID
  • Syllabus for relevant courses
Specialization Notes

Requirements are standardized across the Faculty of Science and Engineering (Institute of Technology) for international Master's programs.