Computer Vision related posts
When you develop a new deep learning model, it should be trained with a huge input dataset. When the input training dataset size is small for computer vision applications, the performance of the model can be increased with Image augmentation. Image augmentation is process of creating new dataset from the existing images with few image […]
Transfer learning is a process in Machine Learning to reuse models that are already developed and trained with the huge dataset. Transfer learning is widely used in computer vision applications because the models are pre-trained with the Imagenet database. it is a widely accepted technique, popular in machine learning because training a model needs a […]
Image segmentation is an essential operation for extracting objects and features from an image. In general object- extraction is an important step in different advanced image processing operations. Among many different ways of segmentation, thresholding is one of the segmentation which produces a binary image. The binary image is an image with pixel values either […]
OpenCV or Open Computer Vision Library is one of the widely accepted opensource Library for image processing and computer vision applications. OpenCV supports Python, this feature makes OpenCV as the default choice for Deep learning application for computer vision. This blog post shows how basic image processing operations can be carried out using Python OpenCV […]