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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.
Education training process falls into three general categories: 1) Instructor Support Products: These are used through teachers additionally to text books, lectures and other
Explain Positioning Techniques in computer Graphics in detail
Q. Explain about Unified Memory Architecture? UMA signifies Unified Memory Architecture. It is an architecture that reduces the cost of PC construction. In this a part of main
Lossless Audio Formats: Lossless audio formats as TTA and FLAC give a compression ratio of around 2:1, sometimes extra. During exchange, for their lower compression ratio, such co
In this project, the image data set consists of 320 training images and 285 test images. Table 1 shows the image data set in details. In addition to the original images, th
are you a robot
2-dimensional xy-shearing transformation, as explained in equation (19), can also be simply extended to 3-dimensional case. All coordinates are translated as a function of displace
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Question: (a) Explain the importance of knowing and understanding your target market before doing a design work. Use example(s) to enhance your answer. (b) Describe the
Cohen Sutherland algorithm Point clipping is very simple. All you need to check is whether a point is inside the window extremes in x- and y-directions. For line clipping sev
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