Extracting the needed portion from a bounded region is an important task in image processing. Editing a map and extracting a region from the map is challenging. It is useful in some contexts to have a region in a separate sheet. In this image processing, we have used the Flood Fill algorithm to extract a region from the image map. To achieve that goal, we had worked in our study to separate a bounded region on a map. Usually, a scanned map may contain a lot of useless information. So we have to process the image to remove useless information from the map. We had quantized the image to a binary one. In the second phase, we have applied a gray color to separate the desired position from a map. Our main objective of the study to extract a bounded region from mapping an image that contains useless information and removes it. We have experimented with several maps and it works successfully.
Students’ academic achievement plays a significant role in the polytechnic institute. It is an important task for the technical student to achieve good results. It becomes more challenging by virtue of the huge amount of data in the polytechnic student databases. Recently, the lack of monitoring of academic activities and their performance has not been harnessed. This is not a good way to evaluate the academic performance of polytechnic students in Bangladesh at present. The study on existing academic prediction systems is still not enough for the polytechnic institutions. Consequently, we have proposed a novel technique to improve student academic performance. In this study, we have used the deep neural network for predicting students' academic final marks. The main objective of this paper is to improve students' results. This paper also explains how the prediction deep neural network model can be used to recognize the most vital attributes in a student's academic data namely midterm_marks, class_ test, attendance, assignment, and target_ marks. By using the proposed model, we can more effectively improve polytechnic student achievement and success.
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