• Assist rchgit git submission: https://github.com/DeLaSalleUniversity-Manila/imagesuper-resolutionviasparserepresentationdemo-rchgit
• Sazerdragon git submission: (https://github.com/DeLaSalleUniversity-Manila/MicroexpressionsSparseSuperResolution-Sazerdragon)
• State-of-the-art SR paper review: http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Huang_Single_Image_Super-Resolution_2015_CVPR_paper.pdf

Fork repo: https://github.com/DeLaSalleUniversity-Manila/SelfExSR

• Current status of own algorithm: average PSNR of around 16dB ( below par ).

1. Specific SR dataset domain for rchgit and sazerdragon.

2. Initial paper draft.

3. Thesis title? (probably)

• Provide another implementation of state-of-the-art SR algorithm (among the 5 recent algorithms (minus A+ since it's the 1st submission))

• Fork from rhgit (https://github.com/DeLaSalleUniversity-Manila/COE5200)

• Lecture from Prof. Raymond R. Tan, Ph.D., "Getting Published: Basic Principles to Get You Started". (https://github.com/DeLaSalleUniversity-Manila/ThesisMeetingMinutes/blob/master/GettingPublished-BasicPrinciplesToGetYouStarted-DrTan.pdf)

• IEEE Conference paper submission by 11/25/2015
• Use both standard dataset and unique dataset
• Use baseline algorithm (as a guarantee...)