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Computer Vision /Machine Learning Intern Resume Example

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COMPUTER VISION /MACHINE LEARNING INTERN
Objective
I am a computer vision enthusiast and researcher, quick learner and keen to explore the realm of Computer Vision. To be able to work and grow professionally as computer vision engineer in a stable organization where I could contribute my skills. My endeavor and dedication in the job will be helpful in achieving the company goals and objectives.
Summary
Around 3 years of IT experience. 7 months of experience in Computer Vision and Machine Learning, 2 Years of ServiceNow CMDB Analyst.
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Knowledge Base
Object Identification and Recognition techniques
  • Object detectors and descriptors techniques like SIFT, SURF, BRIEF.
  • Face detection algorithm Viola Jones, and recognition technique LBP.
  • Object detection through Hough Transform.
  • Edge detection techniques like Sobel and Canny edge detectors.
  • Harris corner detection.
  • FAST detector.
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Image Preprocessing and Enhancement
  • Normalized graph cut for image segmentation.
  • Laplacian of Gaussian(LoG), Difference of Gaussian(DoG) methods for finding the interest points which are invariant to scale.
  • Experience with PIL, Scikit-image, OpenCV computer vision libraries.
Experience
Computer Vision /Machine Learning InternMar 2017 to Current
Advance Solutions － City , STATE

  • Experience with common Machine Learning Algorithms like Regression, Classification and Ensemble models.
  • Implemented Normalization and Standardization preprocessing techniques for models like regression and KNN to reduce the loss.
  • Performed Grid search for a better choice of Hyper parameters.
  • Implemented different CNN architectures like a sequence of Convolutions, Pooling, Activation functions to improve the accuracy.
  • Applied Image Morphological operations like Dilation and Erosion
  • Applied Image enhancement operations like contrast, color-balance, and sharpening to get the meaningful data from the image.  
  • Normalized the image intensity by histogram equalization to increase the image contrast.
  • Reduced the noise by averaging the images.
  • Applied Gaussian blurring filters for blurring, image interpolation, finding the interesting points.
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Skills

CV Libraries: PIL, Scikit-Image, OpenCV
Deep Learning Libraries: Tensorflow, Keras
Machine Learning Libraries: Sci-kit learn, Numpy, Pandas, Scipy, Matplotlib 
Languages: Python  
Education and Training
Master of Science, Industrial Engineering2015Texas A&M, Kingsville － City, State, USA3.75/4 GPA
Professional Experience
Advance Solutions, April 17 to Present | MSCI INC, May 2016 to March 2017 | Stanford Health Care, Feb 2015 to May 2016
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Resume Overview

School Attended

  • Texas A&M, Kingsville

Job Titles Held:

  • Computer Vision /Machine Learning Intern

Degrees

  • Master of Science , Industrial Engineering 2015

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