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The image classification is the process to categorize images into one of several classes or categories. In this project, there are seven categories (Piano, Kangaroo, Strawberry, Sunflower, Airplane, Face and Leopard). Classification requires training for each image category. The image categories are learned through a training process and an image is annotated in terms of the learned categories. Figure 1 shows the overall process of the image classification. This image classification can be used for automatic generation of keyword metadata and for efficient searching and leverage of archived content.
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Introduction of 2-D and 3-D Transformations In this, the subsequent things have been discussed in detail as given below: Different geometric transformations as transla
State the purpose of scan conversion , along with the side effects
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Main Objectives: Interfacing LCD to the Micro-controller (PIC18F4520) Programming LCD by using C- language via MPLAB Sending data or command to the LCD Component
Draw the five regular polyhedras using physics-based modeling method. Implement a fractal algorithm with possible personal extensions. Also, specify the extensions.
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Steps uses in the Cohen Sutherland Line Clipping Algorithm are: Figure: Steps for Cohen Sutherland Line Clipping STEP 1: Input: x L , x R , y T , y B
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How does the Cyrus Beck line clipping algorithm, clip a line segment whether the window is non convex? Solution : see the following figure 13, now the window is non-convex in s
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