GAN生成对抗网络 基于Tensorflow 实现去噪 以及图片生成 可自己修改图片数据集 以及迭代次数等 内附命令行 小白可上手
Attention-guided CNN for image denoising.pptx2020-02-26
Implementing Modern DevOps-Packt Publishing(2017).pdf2018-02-24
DevOps is the newest revolution in deploying software quickly and efficiently. With a set of automation tools, an orchestration platform, and a few processes, companies can speed up the release cycle of their IT systems by enabling the engineers to do more with fewer resources and become more engaged in the business process. Chapter 1, DevOps in the Real World, shows the place of DevOps in the current engineering department of IT companies and how to align resources to maximize delivery potential. Chapter 2, Cloud Data Centers, compares the different cloud solutions for managing resources (VMs, networks, disks, and so on) on the cloud and on demand. Chapter 3, Docker, teaches about Docker and some of its internals in order to better understand how containerization technologies work. Chapter 4, Continuous Integration, talks about continuous integration technologies that can be used to execute tests across your applications as well as many other actions, as we will see in Chapter 8, Release Management – Continuous Delivery. Chapter 5, Infrastructure as Code, shows how to describe our infrastructure in a way that can be managed as code and apply the SDLC best practices to it in order to ensure its integrity. Chapter 6, Server Provisioning, shows how to use Ansible to manage the configuration of remote servers in order to facilitate the maintenance of a large number of servers that, even though we are going to focus on Kubernetes, are good to know. Chapter 7, Docker Swarm and Kubernetes - Clustering Infrastructure, briefly visits Docker Swarm and then points your attention toward Kubernetes, the most modern container orchestration technology, which is used across the biggest corporations in the world, such as Google. Chapter 8, Release Management – Continuous Delivery, shows how to set up a continuous delivery pipeline on Google Cloud Platform with Kubernetes and Jenkins. Chapter 9, Monitoring, shows how to monitor our software and servers to be the first ones to know about a potential outage very quickly and fix it (potentially) before impacting our customers.
Current unsupervised image-to-image translation techniques struggle to focus their attention on individual objects without altering the background or the way multiple objects interact within a scene. Motivated by the important role of attention in human perception, we tackle this limitation by introducing unsupervised attention mechanisms which are jointly adversarially trained with the generators and discriminators. We empirically demonstrate that our approach is able to attend to relevant regions in the image without requiring any additional supervision, and that by doing so it achieves more realistic mappings compared to recent approaches.
Attention-Based Pedestrian Attribute Analysis.pdf2020-06-30
Attention-Based Pedestrian Attribute Analysis，Attention-Based Pedestrian Attribute Analysis
CCENT Certification All-In-One For Dummies.pdf2019-08-22
Introduction T he CCENT certification is a new, fast-growing certification that tests your knowledge of basic Cisco device-management and networking concepts. It is a great stepping stone to the CCNA certification and other Cisco certification tracks. The CCENT exam tests your knowledge of real-world networking concepts and Cisco features found on most networks today! About This Book CCENT Certification All-In-One For Dummies is designed to be a hands-on, practical guide to help you pass the CCENT certification exam. This book is written in a way that helps you not only understand complex technical content, but also prepares you to apply that knowledge to real-world scenarios. I understand the value of a book that covers the points needed to pass the exam, but I also understand the value of ensuring that the information helps you perform IT-related tasks when you are on the job. That is what this book offers you — key points to pass the exam combined with practical information to help you in the real world, which means that you can use this book in more than one way. ✦ An exam preparation tool: Because my goal is to help you pass the CCENT certification exam, this book is packed with exam-specific information and tips to help you with tricky exam questions. You should understand everything that is in this book before taking the exam, but to identify key points that you must know, look for icons named For the Exam. In those paragraphs, you will find helpful tips on topics you are certain to be tested on. ✦ A reference: Rely on my extensive experience in the IT industry not only to study for (and pass) the exam, but also to help you perform common network-related tasks on the job. I hope you find this book a useful tool that you can refer to time and time again in your career as you configure networks and Cisco devices. Conventions Used in This Book Each chapter in this book has different elements that help you prepare to pass your CCENT, including the following features: 03_647486-intro.indd 103_647486-intro.indd 1 10/15/10 11:18 PM10/15/10 11:18 PM Conventions Used in This Book 2 ✦ Quick Assessments: Located at the beginning of each chapter is a Quick Assessment section that gives a number of questions related to the chapter content for you to assess whether you have the knowledge already in that chapter. It is highly recommended to read all chapters in the book, but if you find you are limited on study time you may want to focus on the topics you know the least about — the Quick Assessments help you determine what topics you know and what you need more work on. ✦ Icons: Look for the icons used in each chapter to draw your attention to information needed for the exam or in the real world. For more details on the icons I use, check out the later section, “Icons Used in This Book.” ✦ Chapter Summary: Found at the end of each chapter, the “Chapter Summary” section covers key points you should remember for the exam. ✦ Labs: Lab exercises offer the opportunity to get your hands dirty with a particular topic with real-world experience performing specific tasks. In order to totally grasp the topics discussed in a chapter, be sure to perform the lab exercises. The CCENT certification has a number of simulators that will test your real-world knowledge so you really need to know how to perform the different tasks to pass the exam. Due to the fact that you may have different configurations when you do the labs, there are no lab answers within the Labs section. ✦ Prep Test: Following each “Chapter Summary” section, you can find questions to help review the chapter content and prepare you for the CCENT certification exam. Be sure to answer the review questions in each chapter! Then, after you finish reading the entire book and do the lab exercises, check out the practice exams on the companion CD-ROM, which is designed to function like the real exam, with the same level of difficulty. ✦ Monofont text: To help you distinguish commands you type or text you should see on the screen I apply the monofont style to the text. Examples where you see this style are on router commands, IP addresses, and names of devices. ✦ Boldface text: To help identify new commands that you are learning within a code listing the boldface text style is applied. Although you should read over all code in a code example, using the boldface text will help draw your attention to the new commands presented in a code listing.
Next Item Recommendation with Self-Aention-重要.pdf2019-11-29
Next Item Recommendation with Self-Attention 自我注意力机制的推荐系统
Blockchain is receiving increasing attention from academy and industry, since it is considered a breakthrough technology that could bring huge benefits to many different sectors. In 2017, Gartner positioned blockchain close to the peak of inflated expectations, acknowledging the enthusiasm for this technology that is now largely discussed by media. In this scenario, the risk to adopt it in the wake of enthusiasm, without objectively judging its actual added value is rather high. Insurance is one the sectors that, among others, started to carefully investigate the possibilities of blockchain. For this specific sector, however, the hype cycle shows that the technology is still in the innovation trigger phase, meaning that the spectrum of possible applications has not been fully explored yet. Insurers, as with many other companies not necessarily active only in the financial sector, are currently requested to make a hard decision, that is, whether to adopt blockchain or not, and they will only know if they were right in 3–5 years. The objective of this paper is to support actors involved in this decision process by illustrating what a blockchain is, analyzing its advantages and disadvantages, as well as discussing several use cases taken from the insurance sector, which could easily be extended to other domains
论文研究-Building P2P Course Discussion System.pdf2019-08-15
Building P2P Course Discussion System，Shadi Ibrahim，郭庆平，The popularity of file sharing systems such as Napster , Gnutella  have given enormous attention to the peer-to-peer technology. P2P system combines resource contributions fr
Bayesian Analysis with Python-Packt Publishing(2016).epub2018-01-23
Bayesian statistics has been around for more than 250 years now. During this time it has enjoyed as much recognition and appreciation as disdain and contempt. Through the last few decades it has gained more and more attention from people in statistics and almost all other sciences, engineering, and even outside the walls of the academic world. This revival has been possible due to theoretical and computational developments. Modern Bayesian statistics is mostly computational statistics. The necessity for flexible and transparent models and a more interpretation of statistical analysis has only contributed to the trend. Here, we will adopt a pragmatic approach to Bayesian statistics and we will not care too much about other statistical paradigms and their relationship to Bayesian statistics. The aim of this book is to learn about Bayesian data analysis with the help of Python. Philosophical discussions are interesting but they have already been undertaken elsewhere in a richer way than we can discuss in these pages. We will take a modeling approach to statistics, we will learn to think in terms of probabilistic models, and apply Bayes' theorem to derive the logical consequences of our models and data. The approach will also be computational; models will be coded using PyMC3—a great library for Bayesian statistics that hides most of the mathematical details and computations from the user. Bayesian methods are theoretically grounded in probability theory and hence it's no wonder that many books about Bayesian statistics are full of mathematical formulas requiring a certain level of mathematical sophistication. Learning the mathematical foundations of statistics could certainly help you build better models and gain intuition about problems, models, and results. Nevertheless, libraries, such as PyMC3 allow us to learn and do Bayesian statistics with only a modest mathematical knowledge, as you will be able to verify by yourself throughout this book.
An Attention-Based Deep Learning Model for Multiple Pedestrian.pdf2020-04-13
An Attention-Based Deep Learning Model for Multiple Pedestrian
The code does not need to be changed. You only need to configure the environment and install the corresponding libraries to train and test.
DeepDTA_Deep Drug-Target Binding Affinity Prediction2018.pdf2020-03-20
DTI预测领域的高被引lw，发表于2018年. Abstract Motivation The identification of novel drug–target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have been proposed to predict DT interactions have focused on binary classification, where the goal is to determine whether a DT pair interacts or not. However, protein–ligand interactions assume a continuum of binding strength values, also called binding affinity and predicting this value still remains a challenge. The increase in the affinity data available in DT knowledge-bases allows the use of advanced learning techniques such as deep learning architectures in the prediction of binding affinities. In this study, we propose a deep-learning based model that uses only sequence information of both targets and drugs to predict DT interaction binding affinities. The few studies that focus on DT binding affinity prediction use either 3D structures of protein–ligand complexes or 2D features of compounds. One novel approach used in this work is the modeling of protein sequences and compound 1D representations with convolutional neural networks (CNNs).
Attention is all you need
Mitsubishi has a world wide reputation for its efforts in continually developing and pushing back the frontiers of industrial automation. What is sometimes overlooked by the user is the care and attention to detail that is taken with the documentation. However,to continue this process of improvement, the comments of the Mitsubishi users are always welcomed. This page has been designed for you,the reader,to fill in your comments and fax them back to us. We look forward to hearing from you. Fax numbers: Your name.
ISO/IEC 25012：2008 软件工程 - 软件产品的质量要求和评估（SQuaRE） - 数据质量模型 - 完整英文版（20页）
ISO/IEC 25012：2008 软件工程 - 软件产品的质量要求和评估（SQuaRE） - 数据质量模型 - 完整英文版（20页）