Nasrin

Photo by Guillaume de Germain on UnsplashA deep Convolutional Neural Network for more efficient Image RecognitionVGG Network is the basis for one of the most popular image recognition techniques. It is worth learning because it opens a lot of avenues. You need to understand how a Convolutional Neural Network (CNN) to understand VGGNet. If you are not familiar with CNN architecture please feel free to go through this tutorial first:In this article, we will only focus on the implementation part of the VGGNet. So we will…

Photo by Elijah Hiett on UnsplashUsing Canny Edge Detection EfficientlyEdge detection is very common and widely used image processing necessary for many different computer vision applications like data extraction, image segmentation, and in more granular level feature extraction, and pattern recognition. It reduces the level of noise and the number of details in an image but preserves the structure of the image.Canny edge detection in Python is one of the most popular edge detection methods in computer vision. These are…

Photo by Lysander Yuen on UnsplashSimple, Otsu, and Adaptive Thresholding Implementation with ExamplesOne of the most commonly used segmentation techniques is thresholding. It is widely used in computer vision and is very useful to separate the object that we are interested in from the background. This article will focus on the thresholding techniques in OpenCV.There are three different types of thresholding. We will know how they work at a high level and basically focus on how to use them in OpenCV with examples.What is…

Photo by CDC on UnsplashErosion, dilation, opening, closing, morphological gradient, tophat / whitehat, and blackhat explained with examplesIn my last article, I wrote about some basic image processing in OpenCV. Today, we will advance a little bit and work on the morphological operations which are commonly used in image processing. Morphological operations are used to extract the region, edges, shapes, etc.What are Morphological Operations?Morphological operations are performed on binary images. Binary images may contain…

Photo by Shubham Dhage on UnsplashOpenCV for beginners: move or translate, resize, and croppingOne of the most used libraries for handling image processing and manipulation is openCV for Python users. For image classification, object detection, or optical character recognition, any work related to images in the AI world need some kind of image processing and manipulation most of the time. I decided to write a few tutorials on OpenCV.In this tutorial, we will focus on a few basic functions of OpenCV. These are basic and…

Photo by Adrien Converse on UnsplashStep-by-step explanation and examples with complete codeI have several tutorials on Tensorflow where always inbuilt loss functions and layers had been used. But Tensorflow is a lot more dynamic than that. It allows us to write our own custom loss functions and create our own custom layers. So, there are many ways to make highly efficient models in Tensorflow.The best way to learn is by learning by doing. So, we will learn with exercises using a free public dataset that I used in my last…

Photo by Pavel Neznanov on UnsplashWith complete codeI wrote several tutorials on TensorFlow before which include models with Sequential and Functional API, Convolutional Neural Networks, Reinforcement Neural Networks, etc. In this article, we will work on a model using Functional API but it will predict two outputs with one model.If you already know how functional API works, it should be simple for you. If you need a tutorial or a refresher on functional API, this article should help:Let’s dive into the tutorial. First…

Photo by Marlon Maya on UnsplashA detailed tutorialPivot is a very simple function in BigQuery that can be very useful when you need to rotate rows into columns. It uses an aggregate function on rows and converts the categories in rows to columns. There is unpivot function that does totally an opposite operation. If you are a big query user in Google Cloud Platform and haven’t used Pivot and Unpivot functions yet, it is worth learning.This article will focus on explaining Pivot and Unpivot functions with examples. For…

Photo by Viktor Vasicsek on UnsplashManual calculation from a confusion matrix and the syntax of sklearn libraryPrecision, recall, and f1-score are very popular metrics in the evaluation of a classification algorithm. It is very easy to calculate them using libraries or packages nowadays. But I believe it is also important to understand what is going on behind the scene to really understand the output well.If these concepts are totally new to you, I suggest going to this article first where the concepts of precision,…