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Low-Light-Image-Enhacement-1
Matlab Implementation of journal "A fusion-based enhancing method for weakly illuminated images" by XueyangFu, DeluZeng, YueHuang, YinghaoLiao, XinghaoDing, JohnPaisley, Signal Processing Journal, Elsevier, May 2016image-processing-basics-matlab-3
Inverse Filtering, Wiener Filter, Image Restoration, Hough Transform, Image segmentation using watershed, thresholding, region growing and region splitting and merginglow-light-image-enhancement2
Adaptive image enhancement method for correcting low-illumination imagesLITS-Challenge
Liver Tumor Segmentation Challengeimage-processing-basics-matlab
Image Reading, writing, histogram, histogram equalization, local histogram equalization, low pass filter, high pass filter, geometrical transformationTexture-Classification-using-Wavelet-CNN
Texture classification using wavelet CNN in google colabImage-proceessing-basics-matlab-python-2
Image Addition, Multiplication, Division, Subtraction, Fourier Transform, Inverse Fourier transform, convolution, correlation, horizontal, vertical and diagonal line detection, edge detection, sobel, canny, roberts, prewitt, Laplacian of GaussianFood-classification-and-clorie-estimation-GUI
Food classification using Food 101 dataset and its calorie estimation GUIFace-Recognition
Face Recognition with HOG (Histogram of Gradients) and LDB (Local Difference Binary) features using SVM ClassifierCovid-Detection-using-Lung-Xray-Images
Covid19, Pnemonia, or Normal Detection using Lung Xray Imagesimage_processing_basics
Image Reading, writing, histogram, histogram equalization, local histogram equalization, low pass filter, high pass filter, geometrical transformationOptical-Mark-Reader-using-python
OMR Reader using python. The output will be stored in a excel fileBlood-Cancer-Detection-Using-Faster_region-CNN
Faster Region Convolutional Neural Network using pretrained ResNet50 Model MATLAB- Detects and classify Multiple Myeloma (MM) and B-lineage Acute Lymphoblastic Leukemia (B-ALL).Love Open Source and this site? Check out how you can help us