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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.
QUESTION 1. Describe and explain four features of Firewire. 2. Explain clearly what is sampling rate and how does it influences the quality of video produced. 4. In Adobe
Application Interlacing is utilized through all the analogue TV broadcast systems in recent use as: NTSC: 59.94 fields per second, 525 lines, still field drawn first
Phong Model or Phong Specular Reflection Model It is an empirical model that is not based on physics, although physical observation. Phong observed here for extremely shiny su
Define transformation. Explain all basic transformation
Question: A curve shape has three quadratic Bézier curve segments. The curves have been joined sequentially so that continuity of the first derivative of the resulting curve sha
Explain process of displaying objects in raster display and random display. Draw block diagrams of the architecture of both the display systems.
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
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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
In this lab you will learn how to use chrominance1 to segment coloured images. Here you be detecting skin, however, you could use this method to detect other coloured regions in im
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