Object detection has become an interesting and important research topic within computer science. Everyday we are facing increasing volumes of data where one of these types of data that is of great interest are images. This has led to the need for computers to search, recognise and classify relevant images for all forms of applications from military to civil. The fields of neural networks and genetic programming have achieved these goals with varying success. This project will investigate the task of effective and efficient object detection using neural networks and genetic programming. This project will begin by examining a standard neural network system and a standard genetic programming object detection system to determine which system is faster and what approaches should be taken in order to develop a more effective and more efficient object detection system. In the end this project will produce an improved approach that is more effective and more efficient than most traditional object detection systems.