Now that the research report has been completed and submitted, I have some time to share some interesting facts about the research.
- When people ask what I do for my secret research, I say I download images of apples, bananas, irons, scientific calculators, suitcases, crayons, dustbins, pears, plastic bottles, tissue boxes, forks, spoons, laptops, clocks, pillows and blenders.
- I now possess a large collection of images of apples, bananas, irons, scientific calculators, suitcases, crayons, dustbins, pears, plastic bottles, tissue boxes, forks, spoons, laptops, clocks, pillows and blenders. Much time was spent to collect and download these images.
- For the preliminary versions of the classifier, the classifier achieved a classification rate of 70%. Coincidentally, the training set consisted of 70% natural images and 30% synthetic images.
- For the uninformed, point 3 was a consequence of the classifier labeling everything as a natural image, hence achieving a 70% performance. This approach is excellent. By increasing the set of natural images to 99%, the performance can be boosted to 99% !
- Point 4 was a joke.
- The trusty Microsoft Paint was used to perform many tasks for the project. These tasks include converting GIF, PNG, and BMP images into JPEG format, and creating diagrams for the final report.
- Two computers were used for the project. The project could be run exclusively on either the desktop or the laptop computer, but using two computers greatly increase rate of work.
- The increase in rate of work was not due to being able to run multiple simulations simultaneously. Rather, the simulations were mostly done on one computer (the laptop), while the other (the desktop) was used for net research and report writing. Useful work was done on the desktop while the MATLAB program ran on the laptop.
- Using two computers was also cool for report writing. All the data and related papers were displayed on the laptop screen, while the desktop ran only Word. Information could be directly read from the laptop and entered into the report without ALT-TABBING and changing windows constantly.
- I want a dual monitor setup after learning the advantages of point 9.
- I want a dual core system to be able to run my (hypothetical) dual monitor system properly without lagging. This is also to make running simulations less of a pain.
- MATLAB should perform some checks on code integrity before running. Many times, MATLAB would return an error after it had run much of the simulation processing. The error was a simple formatting error located at the last few lines of the code.
More information on the image classifier will be released if anyone is interested.