Convolutional Neural Networks are great at identifying all the information that makes an image distinct. When we train a deep neural network in Caffe to classify images, we specify a multilayered neural network with different types of layers like convolution, rectified linear unit, softmax loss, and so on. The last layer is the output layer … Continue reading How To Extract Feature Vectors From Deep Neural Networks In Python Caffe
Category: Machine Learning
How To Programmatically Create A Deep Neural Network In Python Caffe
When you are working with Caffe, you need to define your deep neural network architecture in a '.prototxt' file. These prototxt files usually consist of hundreds of lines, defining layers and corresponding parameters. Before you start training your neural network, you need to create these files and define your architecture. One way to do this … Continue reading How To Programmatically Create A Deep Neural Network In Python Caffe
Understanding Locally Connected Layers In Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have been phenomenal in the field of image recognition. Researchers have been focusing heavily on building deep learning models for various tasks and they just keeps getting better every year. As we know, a CNN is composed of many types of layers like convolution, pooling, fully connected, and so on. Convolutional … Continue reading Understanding Locally Connected Layers In Convolutional Neural Networks
What Is Local Response Normalization In Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have been doing wonders in the field of image recognition in recent times. CNN is a type of deep neural network in which the layers are connected using spatially organized patterns. This is in line with how the human visual cortex processes image data. Researchers have been working on coming up … Continue reading What Is Local Response Normalization In Convolutional Neural Networks
Understanding Xavier Initialization In Deep Neural Networks
I recently stumbled upon an interesting piece of information when I was working on deep neural networks. I started thinking about initialization of network weights and the theory behind it. Does the image to the left make sense now? The guy in that picture is lifting "weights" and we are talking about network "weights". Anyway, when we implement … Continue reading Understanding Xavier Initialization In Deep Neural Networks
How Are Decision Trees Constructed In Machine Learning
Decision trees occupy an important place in machine learning. They form the basis of Random Forests, which are used extensively in real world systems. A famous example of this is Microsoft Kinect where Random Forests are used to track your body parts. The reason this technique is so popular is because it provides high accuracy with relatively little … Continue reading How Are Decision Trees Constructed In Machine Learning
Deep Learning With Caffe In Python – Part IV: Classifying An Image
In the previous blog post, we learnt how to train a convolutional neural network (CNN). One of the most popular use cases for a CNN is to classify images. Once the CNN is trained, we need to know how to use it to classify an unknown image. The trained model files will be stored as "caffemodel" … Continue reading Deep Learning With Caffe In Python – Part IV: Classifying An Image
Deep Learning With Caffe In Python – Part III: Training A CNN
In the previous blog post, we learnt about how to interact with a Caffe model. In this blog post, we will learn how to train a proper CNN. Up until now, we were dealing with a single layer network. We just defined it in a prototxt file and visualized it easily. If we want our … Continue reading Deep Learning With Caffe In Python – Part III: Training A CNN
Deep Learning With Caffe In Python – Part II: Interacting With A Model
I know that the title looks slightly misleading. If you are thinking that we will be talking about how to interact with fashion models at a coffee shop, you are in for a big surprise! In the previous blog post, we talked about how to define and visualize a single layer convolutional neural network (CNN). In this … Continue reading Deep Learning With Caffe In Python – Part II: Interacting With A Model
Deep Learning With Caffe In Python – Part I: Defining A Layer
Caffe is one the most popular deep learning packages out there. In one of the previous blog posts, we talked about how to install Caffe. In this blog post, we will discuss how to get started with Caffe and use its various features. We will then build a convolutional neural network (CNN) that can be … Continue reading Deep Learning With Caffe In Python – Part I: Defining A Layer
Perpetual Enigma 