Author: Adrian Rosebrock Translator: Zhang Yiran Proofreader: wwl This article is about3700 words, recommended reading time8 minutes. In this article, you will learn how to use siamese networks and the deep learning libraries Keras / TensorFlow to compare the similarity of two images (and whether they belong to the same or different classes). This blog … Read more
Click on the above“Beginner’s Guide to Vision” to selectStar or “Pin” Important content delivered promptly This article is adapted from | OpenCV Academy Introduction to FaceNet Network FaceNet is a face recognition model proposed by Google, and its biggest difference from other face recognition models is that it does not output an intermediate layer, but … Read more
Abstract: Handwritten digit recognition is an important component of artificial intelligence recognition systems. Due to individual differences in handwritten digits, the accuracy of existing recognition systems is relatively low. This paper completes the recognition and application of handwritten digits based on the TensorFlow deep learning framework. First, the TensorFlow deep learning framework is established, and … Read more
Click the above “MLNLP” to select “Star” public account Important content delivered at the first time From | Zhihu Author | Yao Shi Address | https://zhuanlan.zhihu.com/p/63500952 Column | The Path of Learning Non-Convex Optimization Editor | Machine Learning Algorithms and Natural Language Processing [TensorFlow] Source Code Analysis of AdamOptimizer The optimizers in TensorFlow basically inherit … Read more
Author丨Tian Yu Su Zhihu Column丨Machine Learning Link丨https://zhuanlan.zhihu.com/p/27296712 Introduction The second practical code is updated. The previous column introduced the Skip-Gram model in Word2Vec. If you have read it, you can directly start implementing your own Word2Vec model using TensorFlow. This article will use TensorFlow to complete the Skip-Gram model. If you are not familiar with … Read more
During the learning process, I collected relevant flowcharts for each chapter of the book “Deep Learning with TensorFlow: Introduction, Principles, and Advanced Practice.” This makes the knowledge points in the book more intuitive and easier for readers to learn and review. The flowcharts were compiled by a team I encountered before, known as the Code … Read more
Follow the WeChat official account “ML_NLP” Set as “Starred”, important content delivered to you first! ❝ I’ve been looking at the source code of word2vec these days and found that its loss function is not multi-class cross-entropy but NCE. So I checked some information and found this blog post, sharing it here. ❞ First, let’s … Read more
In section 4.4 of the book “Practical Machine Learning Projects with TensorFlow”, the author used skflow. When skflow first came out, it was quite popular, but the interface changed very frequently, leading to a decline in its usage, which also resulted in the code from section 4.4 no longer running. However, in the recently released … Read more
Click on the above“Beginner Learning Vision” to choose to add “Star” or “Top“ Important content delivered in real-time Development Environment Software Version Information: Windows 10 64-bit TensorFlow 1.15 TensorFlow Object Detection API 1.x Python 3.6.5 VS2015 VC++ CUDA 10.0 Hardware: CPU i7 GPU 1050ti To install the TensorFlow Object Detection API framework, see here: The … Read more
Today, I will share the improved model GER-UNet, which is based on the 2020 paper “Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation.” By understanding the ideas behind this model, similar improvements can be made based on VNet. 1. Limitations of Conventional Convolutional Networks 1. Conventional convolutional neural networks can only utilize … Read more