ME606 Digital Signal Processing Assignment

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Reference no: EM132410176

ME606 Digital Signal Processing Assignment

Course Name Master of Engineering (Telecommunications)

School of Information Technology and Engineering - Melbourne Institute of Technology, Australia

Assessment Title - Review of popular signal-processing task

Unit Learning Outcomes covered in this assessment

a. Development and implementation of signal processing.

c. Understand the design of multi-rate signal processing and their applications.

f. Apply discrete wavelet transforms for processing images and audio.

g. Develop understanding of video and audio compression systems.

Assignment on image classification techniques

1. Give an overview of the image classification techniques.

2. Explain a case study for image classification using the sample references in the assignment folder or online resources (include graphs and tables showing the improvements).

3. Discuss your findings.

References -

1. Image Classification in Remote Sensing by Jwan Al-doski, Shattri B. Mansor and Helmi Zulhaidi Mohd Shafri.

2. Image Classi?cation using Random Forests and Ferns by Anna Bosch, Andrew Zisserman and Xavier Munoz.

3. ImageNet Classification with Deep Convolutional Neural Networks by Alex Krizhevsky, Ilya Sutskever and Geoffrey E. Hinton.

4. Compact Feature Learning for Multi-domain Image Classification by Yajing Liu, Xinmei Tian, Ya Li, Zhiwei Xiong and Feng Wu.

Verified Expert

Image classification is one of the popular research field. The application of image classification is important for many real life applications. one of the best applicable area for image classification is autonomous car. The images are acquired from different sources to train image classification model. one of the best source of image is remote sense image or satellite image. Different techniques are applied on the image data for analysis. In this research we analysed remote sense data with supervised techniques such as parallel piped classification, minimum distance to mean classifier, maximum likelihood classification etc.

Reference no: EM132410176

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