Tag:Encoder

  • Intuitive interpretation of neural machine translation

    Time:2020-12-22

    By ReNu Khandelwal What is neural machine translation? Neural machine translation is a technology that translates one language into another. One example is the conversion of English to Hindi. Let’s think about it. If you’re in an Indian village, most of the people there don’t know English. You plan to communicate with the villagers effortlessly. […]

  • Deep clustering by Gaussian mixture variable autoencoders with graph embedding (DGG) based on graph embedding

    Time:2020-12-21

    Depth clustering of Gaussian mixture variational self encoder based on graph embedding Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embedding, DGG Author: karugaji – blog Garden http://www.cnblogs.com/kailugaji/ 1. Introduction This blog post is mainly a summary of the paper “deep clustering by Gaussian mixture variable autoencoders with graph embedding”. This article combines graph […]

  • Detr of Facebook AI, a target detection method based on transformer

    Time:2020-12-14

    By prateek JoshiCompile | VKSource | analytics vidhya introduce Machine learning frameworks or libraries sometimes change the landscape of the field. Today, Facebook has open source such a framework, Detr (detection transformer) In this paper, we will quickly understand the concept of target detection, and then directly study Detr and its benefits. object detection In […]

  • Keras implementation of VAE variational auto encoder

    Time:2020-11-11

    Variational auto encoder (VAE) is a kind of generation model. The training model consists of encoder and decoder. The encoder maps the input samples to a certain low dimensional distribution, which is usually a multivariate Gaussian distribution with independent dimensions. Therefore, the output of the encoder is the mean and logarithmic variance of the Gaussian […]

  • Transformer in NLP

    Time:2020-11-8

    By ReNu KhandelwalCompile | VKSource: toward Data Science In this article, we will discuss the following questions about transformer Why do we need a transformer, and what are the challenges of the sequence 2 sequence model? Transformer and its architecture are introduced in detail In depth study of the terms used in transformer, such as […]

  • Paper notes: deep lab V3+

    Time:2020-11-8

    introduction Deeplab V3 + is the latest version of deeplab for semantic segmentation, which adds a decoder structure similar to u-net idea and adjusts xception in encoder. The article was published by the Google team byLiang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroffff, and Hartwig Adam Original paper Network architecture The overall architecture of the […]

  • Image reconstruction using depth self encoder in pytorch

    Time:2020-10-13

    By Dr. Vaibhav KumarCompile | VKSource | analytics in diamag There are many popular variants of artificial neural networks, which can be used for supervised and unsupervised learning problems. Self encoder is also a variant of neural network, which is mainly used in unsupervised learning. When they have multiple hidden layers in the architecture, they […]

  • Practical guide to tensorflow convolutional neural networks | ibooker · apachecn

    Time:2020-10-8

    Original text:Hands-On Convolutional Neural Networks with TensorFlow agreement:CC BY-NC-SA 4.0 Proud to adoptGoogle Translate Don’t worry about your image, just about how to achieve your goals. ——Principles, living principles 2.3. C Online reading Apachecn interview and job exchange group 724187166 Apachecn learning resources catalog A practical guide to tensorflow convolutional neural networks Preface 1、 Setup […]

  • Tensorflow deep learning Chinese 2nd Edition · translation completed

    Time:2020-9-18

    Deep learning with tensorflow Second Edition Protocol: CC by-nc-sa 4.0 Don’t worry about your image, just about how to achieve your goals. ——Principles, living principles 2.3. C Online reading Apachecn interview and job exchange group 724187166 Apachecn learning resources catalog Tensorflow deep learning Chinese 2nd Edition 1、 Artificial neural network 2、 What are the new […]

  • Django 3.1 asynchronous view first look

    Time:2020-8-20

    Django 3.1 will be released in August 2020! Starting with version 3.1, Django will gradually support asynchronous, such as asynchronous views and middleware. Django 3.1 only supports Python 3.6, 3.7, 3.8, and later. The new features of Django 3.1 are introduced as follows 1. Asynchronous view In django3.1, it’s easy to define an asynchronous view […]

  • Configuration steps of SRT codec with vmix software

    Time:2020-7-1

    1、 Vmix receives the SRT stream pushed by encoder in listener mode1. Open the vmix software, click “add input” – “more” in the lower left corner, and select the “stream / SRT” option. The interface is as follows:2. Select “stream type” as “SRT (listener)”, configure parameters such as “port”, “latency”, “passphrase” (if necessary), and “decoder […]

  • Variational inference and variational self encoder

    Time:2020-6-12

    Variational inference and variational self encoder Author: kailugaji blog Park http://www.cnblogs.com/kailugaji/ This paper mainly introduces the variable auto encoder (VAE) and its derivation process, but VAE involves some basic knowledge of probability and statistics, so in order to better understand VAE, it first introduces the variable inference and expectation maximization, EM) algorithm, and then introduce […]