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GitHub / nive927 / Pothole-and-Plain-Road-Classification

Using deep learning and transfer learning techniques to differentiate plain roads and those with potholes using three different classifiers to obtain the best accuracy with the same convolutional base

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nive927%2FPothole-and-Plain-Road-Classification

Stars: 1
Forks: 1
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 32.2 MB
Dependencies parsed at: Pending

Created at: about 3 years ago
Updated at: over 1 year ago
Pushed at: about 3 years ago
Last synced at: over 1 year ago

Topics: cnn, cnn-classification, cnn-keras, convolutional-neural-networks, deep-learning, detection-model, fully-connected-network, global-average-pooling, linear-svm, machine-learning, performance-metrics, plotting-performance-graphs, pothole-detection, scikit-learn, svm, svm-classifier, svm-model, transfer-learning, vgg16

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