Categorizing on-Screen Laptop Damages by using AI

Abstract

AI has taken machine’s working capacity to a new level where machines are able to make intelligent decisions that sometimes out smart humans. AI based machines think on a broader scale, thus they even think of possibilities humans might not have imagined hence benefiting business of all types. A major and tedious problem faced by ecommerce companies who own warehouses was detecting On-Screen damage, classifying its damage type, and locating where the damage lies on the screen. AI and CV together enabled us to detect On-Screen damage, classifying its damage type and locating where the damage lies on the screen. This project is in collaboration with Expert System Solutions (ESS); ESS provides solutions to the industry. One of the ESS’s clients faces the problem shared above and this project aims to solve this problem. A major challenge is on-screen (power on) damage. On-screen damages are very hard to identify as there are many screen types along with many different types of damages. It’s a complex task to identify the type of damage as reflection, dust or even wallpaper can be a source