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convolutional-neural-networks-cnn

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kanchan88 / disease-detection-CNN

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The Cell can certain features than help doctors to make decision whether you can a certain disease or not. ANN model will take long time for image classification and can only work in images concentrated in center. Here is how you do using CNN(Convolutional Neural Network). CNN is the expanded version of ANN.

cnn disease convolutional-neural-network convolutional-neural-networks-cnn disease-detection-cnn ann-model cnn-example
  • Updated Aug 13, 2020
  • Jupyter Notebook

Joycechidi / MachineLearning2

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Continuation of my machine learning works based on Subjects....starting with Evaluating Classification Models Performance

natural-language-processing reinforcement-learning deep-learning clustering thompson-sampling dimensionality-reduction apriori hierarchical-clustering k-means-clustering association-rule-learning kernel-pca eclat eval-classification-models-perf upper-confidence-bound-ucb natural-language-processing-algo artificial-neural-networks-ann convolutional-neural-networks-cnn principal-component-analysis-pca linear-discriminant-analysis-lda model-selection--xgboost
  • Updated Jul 26, 2018

AKKI0511 / Traffic-Sign-Recognition

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Traffic sign recognition using deep learning. Implemented and compared custom CNN and transfer learning models (ResNet50, MobileNetV2) with comprehensive evaluation metrics. Achieved 98.8% accuracy with a focus on real-world efficiency.

machine-learning computer-vision deep-learning neural-network tensorflow keras artificial-intelligence image-classification transfer-learning data-augmentation model-evaluation cnn-architecture traffic-sign-recognition image-preprocessing model-comparison gpu-optimization resnet50 mobilenetv2 convolutional-neural-networks-cnn
  • Updated Nov 10, 2024
  • Jupyter Notebook

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