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Pattern Recognition and Machine Learning

Course Project

Course Instructor: Dr. Richa Singh

Natural Image Classification (CIFAR 10)

Natural Image Classification is one of the hot topics in computer vision and pattern recognition research. In recent years scene understanding and object classification has received intense attention as it is beneficial for many practical applications such as autonomous driving, robot vision and content-based image retrieval. The project aims at classifying images under 10 labels that includes Airplane, Automobile, Bird, Cat, Deer, Dog, Frog, Horse, Ship and Truck. The classifier used for the project is Convolutional Neural Network which is trained on CIFAR 10 dataset, which came out to be best if compared to KNN, SVM, MLP and Random Forest trained with the same data. The report and the code for training models can be seen here.

Contributors

Name Roll Number Year Department
Deep Ashokbhai Patel B19CSE028 Sophomore Computer Science and Engineering
Maniyar Suyash B19EE095 Sophomore Electrical Engineering
Mohan Chhabaria B19EE096 Sophomore Electrical Engineering

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Languages

  • Python 48.7%
  • HTML 35.6%
  • CSS 9.8%
  • JavaScript 5.9%