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
Follow our public account “ML_NLP“ Set as “Starred“, heavy content delivered to you first! Source | Zhihu Address | https://zhuanlan.zhihu.com/p/31096913 Author | Datartisan Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is any infringement, please contact the background for deletion. This article will … 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
Originally from PaperWeekly Column Introduction:Paddle Fluid allows users to execute programs similarly to PyTorch and Tensorflow Eager Execution. In these systems, the concept of a model no longer exists, and applications no longer contain a symbolic description for the Operator graph or a series of layers, but instead describe the training or prediction process like … Read more
Deep learning is a general term for the process of machine learning using multi-layer neural networks. Multi-layer neural networks are models that utilize various mathematical methods and their combinations. In recent years, people have been able to effectively leverage neural networks primarily due to the reality of obtaining sufficient amounts of data and the rapid … Read more
In 2019, did everyone notice a social phenomenon where competition for AI positions became increasingly fierce?However, at the same time, companies say that there is a severe shortage of AI talent?This seems a bit contradictory, but upon closer examination, the main reason is that many people want to enter the high-paying AI industry, but the … Read more
Today, I will share the improved model DC-UNet, which is based on the U-Net architecture. The improvement comes from the 2020 paper titled “DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation.” By understanding the concept of this model, similar improvements can be made based on VNet. 1. Original UNet … Read more
Abstract In recent years, deep learning has become a hot research topic. Although it can yield unexpectedly positive results in some cases, bugs within deep learning software can lead to catastrophic consequences, especially when the software is used in safety-critical applications. In this paper, we present an empirical study of a typical deep learning library—TensorFlow—analyzing … Read more
Click on the above “3D Vision Workshop“, select “Star” Delivering valuable content promptly Author | Pan Duoduo Source | Deep Learning and Computer Vision Introduction to 3D-CNN The MNIST dataset classification is considered the hello world program in the field of computer vision. The MNIST dataset helps beginners understand the concept and implementation of Convolutional … Read more
Author | Jeff Hale Translator | Jackey Editor | Jane Produced by | AI Technology Camp (id: rgznai100) 【Introduction】 After the release of TensorFlow 2.0 and PyTorch 1.0, the discussion about which of the two is superior has been ongoing and still lacks a definitive conclusion. In this article, the author analyzes data from multiple … Read more