Over the past 20+ years, I have been working as a software engineer, architect, and programmer, creating, designing, and programming various applications. My main focus has always been to achieve business goals and transform business ideas into digital reality. I have successfully solved numerous business problems and increased productivity for small businesses as well as enterprise corporations through the solutions that I created.
My strong technical background and ability to work effectively in team environments make me a valuable asset to any organization.
Descriptive statistics were developed to reduce the list of all the data items to a few simpler numbers. For example, the mean, median, high, low, and standard deviation. The cumulative fraction function displays how the data is distributed, with most data clustered on the left indicating a non-normal distribution. Scaling the x-axis, typically using a log scale for positive data, allows for better visualization. The KS-test computes the maximum vertical deviation between two datasets’ cumulative fraction curves, indicating differences in distribution.
This step performs the following: From input video(s) extracted the frames, which are called mean frames. These mean frames are store on hard disk, used for decision making. Extract the features from mean frames.
After all features calculating these features are send to classification model where these features are used for decision making. Basic theme for all models is same so here only discuss the abstract approach for decision making.
It takes an Image and converts it into gray scale if it is not already in gray scale. For wavelets it apply wavelets HARR on image and return coefficient values.
It takes an Image and converts it into gray scale if it is not already in gray scale. For slope magnitude it checks the per pixel maximum change with its neighbor’s pixels.
