It is essential to have a method to map an unknown terrain for various applications. For places where human access is not possible, a method should be proposed to identify the environment. Exploration, disaster relief, transportation and many other purposes would be convenient if a map of the environment is available. Replicating the human vision system using stereo cameras would be an optimum solution. In this work, we have used laser ranging based technique fused with stereo cameras to extract dimension of objects for mapping. The distortions were calibrated using mathematical model of the camera. By means of Semi Global Block Matching [1] disparity map was generated and reduces the noise using novel noise reduction method of disparity map by dilation. The Data from the Laser Range Finder (LRF) and noise reduced vision data has been used to identify the object parameters.

For the purpose of this project, I used 2 supervised machine learning methods. I compared several classification and regression models on how well they are able to identify future donors and estimate how much they will donate. These models were used to predict the outcome of the next campaign. Yemego NGO is a fictitious charity organization that provides programs and services for veterans with spinal cord injuries or diseases. Direct mailing campaigns are used to raise funds for charity organizations.