you'll study an area of computer vision in significant depth. All projects should involve reading research literature, implementing a computer vision system, evaluating that system, and comparisons with the literature. Projects can be done individually or in teams of two. You should outline the tasks from each team member in your project selection statement (expected tasks), and the final report.
1. Use a combination of convolutional neural networks and local binary patterns for hyperspectral image classification.
Wei, Xiangpo, Xuchu Yu, Bing Liu, and Lu Zhi. "Convolutional neural networks and local binary patterns for hyperspectral image classification." European Journal of Remote Sensing 52, no. 1 (2019): 448-462.
2. ICPR 2020 challenge problem: Develop a system for automatic classification of pollen grain images.
https://iplab.dmi.unict.it/pollenclassificationchallenge/
3. ISBI 2021 challenge problem: Retinal image analysis for multi-disease detection challenge.
https://riadd.grand-challenge.org/
4. Other Topics: Students are encouraged to suggest a topic of their interest. Example problems include topics like image enhancement, inpainting, compression, and denoising. Projects that overlap with your research are generally fine.
It’s not expected to test the performance on all datasets and experiments mentioned, you can also test your proposed model on similar datasets you find.
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