Image Segmentation + genetic programming
Budget: $30 – $250 USD
I want to do like this one:
https://youtu.be/sR-2KXuaQRw
but genetic programming will be used instead on nural network.
-the project is all done using matlab, and every single line has to be explained "what it does , why it's used" documented and explained
-we will develop a genetic programming system that you enter MRI photo for brain tumor
-program will target the tumor and calculate its size
-genetic programming will be using for this process
Genetic programming, uses four steps to solve problems:
1) Generate an initial population of random compositions of the functions and terminals of the problem (computer programs).
2) Execute each program in the population and assign it a fitness value according to how well it solves the problem.
3) Create a new population of computer programs.
i) Copy the best existing programs
ii) Create new computer programs by mutation.
iii) Create new computer programs by crossover
4) The best computer program that appeared in any generation, the best-so-far solution, is designated as the result of genetic programming
-Each program is GRAPH CUT using different equation
-The Graph Cut has to be implemented from scratch not imported so we can calculate the performance of different euqations and the code has to be clear so it can be modified
Available budget is 250 dollars.maximum for all of above
https://youtu.be/sR-2KXuaQRw
but genetic programming will be used instead on nural network.
-the project is all done using matlab, and every single line has to be explained "what it does , why it's used" documented and explained
-we will develop a genetic programming system that you enter MRI photo for brain tumor
-program will target the tumor and calculate its size
-genetic programming will be using for this process
Genetic programming, uses four steps to solve problems:
1) Generate an initial population of random compositions of the functions and terminals of the problem (computer programs).
2) Execute each program in the population and assign it a fitness value according to how well it solves the problem.
3) Create a new population of computer programs.
i) Copy the best existing programs
ii) Create new computer programs by mutation.
iii) Create new computer programs by crossover
4) The best computer program that appeared in any generation, the best-so-far solution, is designated as the result of genetic programming
-Each program is GRAPH CUT using different equation
-The Graph Cut has to be implemented from scratch not imported so we can calculate the performance of different euqations and the code has to be clear so it can be modified
Available budget is 250 dollars.maximum for all of above