Psych221-Projects-2018-Fall

From Psych 221 Image Systems Engineering
Revision as of 18:24, 14 December 2018 by imported>Student2018 (→‎Project write-ups. Fall 2018)
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Launch page for Psych 221 Projects in Fall, 2018


Return to Psych 221 Main


There are two deliverables for the project:

  1. A group presentation
  2. A wiki-style project page write-up

To set up your project's page

  • Log in to the wiki
  • Edit the Projects section of this page. Do this by clicking on "[edit]" to the right of each section title.
  • Copy the example project title and group names
  • Paste in a new line under the last item/group
  • Edit the project title and group members. Note that the first part of the text in double brackets is the actual link and must be unique. Putting all your names is the safest way to assure this. The second part, after '|' is the displayed text.
  • Save page by clicking at the bottom
  • Clicking on the link you entered will create a blank page for your project

Project write-ups. Fall 2018

Please place your project pages below:

  1. This is a sample project title
    • Brian Wandell, Joyce Farrell, Trisha Lian.
  1. Predicting Sensor Response Using Convolutional Neural Networks
    • Ed Ng
  1. Exploring IR Colorization Using Machine Learning
    • YC LJ
  1. Retinal Magnification Factor as a Function of Eccentricity among Different Schematic Eye Models
    • zzx
  1. Google HDR+ Image Processing Pipeline
    • Jennifer Chih-Wen Lin, Linda Banh, Warren Cheng
  1. Image Upsampling using L3
    • Rituraj, Siddharth Buddhiraju.
  1. Google HDR pipeline Implementation in Matlab
    • Zhihan Jiang, Yicheng Li, Wensi Yin
  1. Characterization of Power LED Non-uniformity for Spectrophotometry Applications
    • Brian Jun
  1. Spatial CIELAB vs ISETBio and Front-End Physiological Optics
    • Lars Jebe, Joe Sommer
  1. Training the linear, local, learned (L3) for imaging in low light conditions
    • Zheng Lyu, Zhanghao Sun
  1. IR
    • Minda Deng, Yuxin Hu
  1. Creating an Automated Image Processing Pipeline using a Convolutional Neural Network
    • Shreyash Pandey, Viraga Perera, Anand Venkatesan.
  1. Autofluorescence in the Oral Cavity
    • Alyssa Cartwright
  1. Automated Attendance System Using Deep Learning
    • Elizabeth Botbol Ponte and Jenya Pergament