In this article, we will try to convert a normal photo into a pencil sketch using computer vision in a python programming language. In this article, we will show how to convert an image into its corresponding pencil sketch in a few steps.
In this article, we will build the same deep learning framework that will be a convolutional neural network for image classification on the same dataset in Keras, PyTorch and Caffe and we will compare the implementation in all these ways. Finally, we will see how the CNN model built in PyTorch outperforms the peers built-in Keras and Caffe.
Computer vision is one of the most trending subfields in Artificial Intelligence because of its wide variety of applications. In some domains, they even suppress
In simple terms, computer vision enables our computer to process and visualize the data. It is a very complicated task to make the computer learn
Skorch is one of the useful libraries in Pytorch to work on machine learning models especially neural networks. It is a robust library that works
The loss function is a method of evaluating how well the algorithm performs on your dataset, most of the people are confused about the difference
Throughout this article, we will discuss these optimization techniques with their intuition and implementation.
By using SQLALchemy instead of learning a database programming language we can directly write queries for creating, manipulations, retrieving data, updating records using simple python scripts.
My first Web Scraping project – Analyzing Flipkart Product Reviews using Text Mining – Scrape and Analyze customer reviews
Throughout this article, we will discuss the importance of the ‘argmax()’ function and demonstrate its implementation through examples.
Through this article, we will discuss how the batch normalization helps in building an efficient model. Batch normalization is a feature that we add between the layers of the neural network and it continuously takes the output from the previous layer and normalizes it before sending it to the next layer. This has the effect of stabilizing the neural network. Batch normalization is also used to maintain the distribution of the data.
Through this article, we will demonstrate the implementation of HarDNet – a deep learning framework – using pre-trained weights which are already trained on ImageNet dataset.
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