Master of Science in Electrical Engineering- Communications and Signal Processing (Image Analysis and Computer Vision )
国际学生入学条件
Applicants must have a Bachelor's degree from an accredited college or university in Electrical Engineering, Computer Engineering or a closely related field. The ECE Department prefers that applicants have an undergraduate GPA of 3.25 or higher. The Graduate School requires applicants to have a GPA of 3.0 or higher. Applicants must upload one transcript from each college and university they have attended. Each transcript must include all courses completed and the degrees and dates awarded, if applicable. Applicants who have attended North Carolina State University are not required to provide an NC State transcript. This statement should be about the applicant's academic career, research experience and career goals. Upload the statement in the Personal Statement/Statement of Purpose section of the online application. Three letters of recommendation are required. GRE General Exam Scores , IELTS Test Section 6.5 points Listening 6.5 points, Reading 6.5 points, Writing 6.5 points, Speaking 7.0 points , ECE Department Required Minimum Scores Internet-based Test (IBT) Listening 18 points, Reading 18 points, Writing 18 points, Speaking 19 points , Total 90 points for admission
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雅思考试总分
6.5
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- 雅思总分:6.5
- 托福网考总分:90
- 托福笔试总分:160
- 其他语言考试:NA
课程简介
Computer image analysis largely contains the fields of computer or machine vision, and medical imaging, and makes heavy use of pattern recognition, digital geometry, and signal processing. This field of computer science developed in the 1950s at academic institutions such as the MIT A.I. Lab, originally as a branch of artificial intelligence and robotics.<br><br>Computers are indispensable for the analysis of large amounts of data, for tasks that require complex computation, or for the extraction of quantitative information. On the other hand, the human visual cortex is an excellent image analysis apparatus, especially for extracting higher-level information, and for many applications including medicine, security, and remote sensing human analysts still cannot be replaced by computers. For this reason, many important image analysis tools such as edge detectors and neural networks are inspired by human visual perception models.<br><br>Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images or multi-dimensional data. Information is that which enables a decision. Since perception can be seen as the extraction of information from sensory signals, computer vision can be seen as the scientific investigation of artificial systems for perception from images or multi-dimensional data.
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