指南：想成为一个JSP网站程序员吗？_MySQL

This AI-assisted programming tool has unearthed a large number of useful AI-assisted programming tools in this stage of rapid AI development. AI-assisted programming tools can improve development efficiency, improve code quality, and reduce bug rates. They are important assistants in the modern software development process. Today Dayao will share with you 4 AI-assisted programming tools (and all support C# language). I hope it will be helpful to everyone. https://github.com/YSGStudyHards/DotNetGuide1.GitHubCopilotGitHubCopilot is an AI coding assistant that helps you write code faster and with less effort, so you can focus more on problem solving and collaboration. Git

This paper explores the problem of accurately detecting objects from different viewing angles (such as perspective and bird's-eye view) in autonomous driving, especially how to effectively transform features from perspective (PV) to bird's-eye view (BEV) space. Transformation is implemented via the Visual Transformation (VT) module. Existing methods are broadly divided into two strategies: 2D to 3D and 3D to 2D conversion. 2D-to-3D methods improve dense 2D features by predicting depth probabilities, but the inherent uncertainty of depth predictions, especially in distant regions, may introduce inaccuracies. While 3D to 2D methods usually use 3D queries to sample 2D features and learn the attention weights of the correspondence between 3D and 2D features through a Transformer, which increases the computational and deployment time.

VSCode Setup in Chinese: A Complete Guide In software development, Visual Studio Code (VSCode for short) is a commonly used integrated development environment. For developers who use Chinese, setting VSCode to the Chinese interface can improve work efficiency. This article will provide you with a complete guide, detailing how to set VSCode to a Chinese interface and providing specific code examples. Step 1: Download and install the language pack. After opening VSCode, click on the left

On March 3, 2022, less than a month after the birth of the world's first AI programmer Devin, the NLP team of Princeton University developed an open source AI programmer SWE-agent. It leverages the GPT-4 model to automatically resolve issues in GitHub repositories. SWE-agent's performance on the SWE-bench test set is similar to Devin, taking an average of 93 seconds and solving 12.29% of the problems. By interacting with a dedicated terminal, SWE-agent can open and search file contents, use automatic syntax checking, edit specific lines, and write and execute tests. (Note: The above content is a slight adjustment of the original content, but the key information in the original text is retained and does not exceed the specified word limit.) SWE-A

Go language development mobile application tutorial As the mobile application market continues to boom, more and more developers are beginning to explore how to use Go language to develop mobile applications. As a simple and efficient programming language, Go language has also shown strong potential in mobile application development. This article will introduce in detail how to use Go language to develop mobile applications, and attach specific code examples to help readers get started quickly and start developing their own mobile applications. 1. Preparation Before starting, we need to prepare the development environment and tools. head

As a fast and efficient programming language, Go language is widely popular in the field of back-end development. However, few people associate Go language with front-end development. In fact, using Go language for front-end development can not only improve efficiency, but also bring new horizons to developers. This article will explore the possibility of using the Go language for front-end development and provide specific code examples to help readers better understand this area. In traditional front-end development, JavaScript, HTML, and CSS are often used to build user interfaces

In September 23, the paper "DeepModelFusion:ASurvey" was published by the National University of Defense Technology, JD.com and Beijing Institute of Technology. Deep model fusion/merging is an emerging technology that combines the parameters or predictions of multiple deep learning models into a single model. It combines the capabilities of different models to compensate for the biases and errors of individual models for better performance. Deep model fusion on large-scale deep learning models (such as LLM and basic models) faces some challenges, including high computational cost, high-dimensional parameter space, interference between different heterogeneous models, etc. This article divides existing deep model fusion methods into four categories: (1) "Pattern connection", which connects solutions in the weight space through a loss-reducing path to obtain a better initial model fusion

Written above & The author’s personal understanding is that image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of an object or scene from a set of input images. Learning-based methods have attracted attention for their ability to directly estimate 3D shapes. This review paper focuses on state-of-the-art 3D reconstruction techniques, including generating novel, unseen views. An overview of recent developments in Gaussian splash methods is provided, including input types, model structures, output representations, and training strategies. Unresolved challenges and future directions are also discussed. Given the rapid progress in this field and the numerous opportunities to enhance 3D reconstruction methods, a thorough examination of the algorithm seems crucial. Therefore, this study provides a comprehensive overview of recent advances in Gaussian scattering. (Swipe your thumb up