PICSTOR

dc.contributor.authorMuneeb Shahzad
dc.contributor.authorLHR TP 7510
dc.contributor.authorMr. Shuja Akbar
dc.contributor.authorFA17-BCS-123
dc.date.accessioned2026-02-26T06:47:05Z
dc.date.issued2021
dc.description.abstractPeople love to capture their special moments in form of pictures. These days, smartphone photography has become so common that it has overtaken digital camera. Although, with a smartphone, you can capture your special occasions at just click of a button but its capabilities are still limited due to computational and hardware limits. Therefore, this project aims to overcome these limitations and enhance users’ experience by implementing various computer vision and machine learning techniques. Moreover, the project is divided into parts – improved picture quality, portrait mode effect, facial feature editing and fun features/filters. All these features will make phone photography more fun and exciting.
dc.identifier.urihttps://repository.cuilahore.edu.pk/handle/123456789/2335
dc.language.isoen_US
dc.publisherLibrary Information Services, CUI Lahore
dc.subjectPICSTOR
dc.titlePICSTOR
dc.typeThesis

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
7510.pdf
Size:
1.87 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
319 B
Format:
Item-specific license agreed to upon submission
Description: