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images
images
 
 
2.1.1_Images_with_python_library_PIL.ipynb
2.1.1_Images_with_python_library_PIL.ipynb
 
 
2.1.2_Images_with_python_library_OpenCV.ipynb
2.1.2_Images_with_python_library_OpenCV.ipynb
 
 
2.2.1_basic_image_manipulation_PIL.ipynb
2.2.1_basic_image_manipulation_PIL.ipynb
 
 
2.2.2_basic_image_manipulation_open_CV.ipynb
2.2.2_basic_image_manipulation_open_CV.ipynb
 
 
2.3.2_Histograms_and_Intensity_Transformations.ipynb
2.3.2_Histograms_and_Intensity_Transformations.ipynb
 
 
2.4.1_Gemetric_trasfroms_PIL.ipynb
2.4.1_Gemetric_trasfroms_PIL.ipynb
 
 
2.4.2_Gemetric_trasfroms_OpenCV.ipynb
2.4.2_Gemetric_trasfroms_OpenCV.ipynb
 
 
2.5.1_Spatial_Filtering-PIL.ipynb
2.5.1_Spatial_Filtering-PIL.ipynb
 
 
2.5.2_Spatial_Filtering_OpenCV.ipynb
2.5.2_Spatial_Filtering_OpenCV.ipynb
 
 
3.1.1_Train_Classification_KNN.ipynb
3.1.1_Train_Classification_KNN.ipynb
 
 
3.1.2_Use_Classification_KNN.ipynb
3.1.2_Use_Classification_KNN.ipynb
 
 
3.2.1_Logistic_Regression_With_Mini-Batch_Gradient_Descent.ipynb
3.2.1_Logistic_Regression_With_Mini-Batch_Gradient_Descent.ipynb
 
 
3.2.2_Digit_Classification_with_Softmax.ipynb
3.2.2_Digit_Classification_with_Softmax.ipynb
 
 
3.2.3_Support_Vector_Machines_vs_Vanilla_Linear_Classifier.ipynb
3.2.3_Support_Vector_Machines_vs_Vanilla_Linear_Classifier.ipynb
 
 
3.3.1_Train_Classification_SVM_HOG.ipynb
3.3.1_Train_Classification_SVM_HOG.ipynb
 
 
3.3.2_Use_Classification_SVM_HOG.ipynb
3.3.2_Use_Classification_SVM_HOG.ipynb
 
 
4.1.1_Simple_Neural_Network_for_XOR.ipynb
4.1.1_Simple_Neural_Network_for_XOR.ipynb
 
 
4.1.2_Neural_Network_RELU_vs_Sigmoid.ipynb
4.1.2_Neural_Network_RELU_vs_Sigmoid.ipynb
 
 
4.1.3_Training_a_Neural_Network_with_Momentum.ipynb
4.1.3_Training_a_Neural_Network_with_Momentum.ipynb
 
 
4.2.1_CNN.ipynb
4.2.1_CNN.ipynb
 
 
4.2.2_Data_Augmentation.ipynb
4.2.2_Data_Augmentation.ipynb
 
 
4.3.1_Train_Classification_CNN_Pytorch.ipynb
4.3.1_Train_Classification_CNN_Pytorch.ipynb
 
 
5.1.1_Use_Object_Detection_Haar_Car.ipynb
5.1.1_Use_Object_Detection_Haar_Car.ipynb
 
 
5.1.2_Use_Object_Detection_Faster_R_CNN.ipynb
5.1.2_Use_Object_Detection_Faster_R_CNN.ipynb
 
 
6.1.1_Train_Classification_CNN_PyTorch.ipynb
6.1.1_Train_Classification_CNN_PyTorch.ipynb
 
 

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This repository contains my practice of Introduction to Computer Vision and Image Processing lab notebooks.

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convolutional-neural-networkscv-studiodeep-neural-networksdeploy-modelibm-cloudimage-classificationimage-processingimage-segmentationobject-detectionopencvpillowpythonpytorchsupervised-machine-learningtensorflowtest-modeltrain-modeltransfer-learninguse-model
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