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Object Detection using Transfer Learning in MATLAB

Ritwik Raha

Ritwik Raha

Kolkata, West Bengal

3 0
  • 0 Collaborators

Using the resnet-50 model on the caltech101 image dataset to classify images and detect objects semantically. ...learn more

Project status: Published/In Market

Artificial Intelligence

Code Samples [1]

Overview / Usage

This example shows how to use transfer learning to retrain ResNet-50, a pretrained convolutional neural network, to classify a new set of images.In this case the network is used to identify objects from the Caltech-101 dataset. Transfer learning is commonly used in deep learning applications. One can take a pretrained network and use it as a starting point to learn a new task. Fine-tuning a network with transfer learning is usually much faster and easier than training a network with randomly initialized weights from scratch.

Methodology / Approach

Object Detection has been achieved by implementing the following steps in MATLAB

  • Loading the data from the dataset
  • Loading the pretrained network
  • Replace the final layers
  • Split the data into testing and training data
  • Train the network
  • Classify Validation images
  • Obtain accuracy

Technologies Used

  • Matlab 2018b
  • Deep Learning Toolbox
  • Resnet-50 architecture
  • Caltech-101

Repository

https://github.com/ritwikraha/Object-Detection-using-Transfer-Learning

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