Category:AI
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Configuration and operation of the M2DGR dataset on some SLAM frameworks: ORB-SLAM series, VINS-Mono, LOAM series, FAST-LIO series, hdl_graph_slam
Article Catalog I. The M2DGR dataset(ii) ORB-SLAM22.1 Configuration parameters2.2 Monocular Three, ORB-SLAM33.1 Configuration parameters3.2 Operational monocular + IMU 4, VINS-Mono4.1 Configuration parameters4.2 Operational monocular + IMU V. DM-VIO5.1 Installation5.2 Configuration runs VI. A-LOAM7, LeGO-LOAM8, LIO-SAM8.1 Configuration parameters8.2 Operation Nine, LVI-SAM9.1 Configuration parameters9.2 Operation 10, LINS10.1 Installation10.2 Configuration parameters10.3 Operation XI. FAST-LIO211.1 Installation11.2 Configuration parameters11.3 Operation […]
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Tensorflow-gpu nanny-level installation tutorial (Win11, Anaconda3, Python3.9)
Tensorflow-gpu Nanny Installation Tutorial (Win11, Anaconda3, Python3.9) preamblePreparation for Tensorflow-gpu version installation(a) Check the computer’s video card:(ii), Anaconda installation(iii) cuda download and installation(D), cudnn download and installation(v) Configuration of environment variables(F), create tensorflow environment(VII), test whether Tensorflow-gpu is installed successfully or notuninstall and reinstall preamble CPUversions andGPUThe differences between the versions are mainlyrunning speed,GPUVersion Running […]
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Installing tensorflow on Windows
Article Catalog I. Environmental configuration1.1 Installing python 3.81.2 Installing Miniconda1.3 Installing Visual C++ Second, install Tensorflow I. Environmental configuration Installation: python 3.8, Miniconda, Visual C++ 1.1 Installing python 3.8 go intopython official websiteInstallation DownloadWindows installer (64-bit)(The version I downloaded) 1.2 Installing Miniconda go intoMiniconda websiteInstallation DownloadMiniconda3 Windows 64-bit(I downloaded the version) Note that the version […]
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NLP Large Model Fine-Tuning Principles
1. Background LLM (Large Language Model) Large Language Model, designed to understand and generate human language, needs to be trained on a large amount of text data. It is generally based on the Transformer structure and has a parameter count of Billion or more. For example, GPT-3 (175B), PaLM (560B). Three big things are happening […]
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AttributeError: module ‘numpy‘ has no attribute ‘object‘
The one I have is calling some component of numpy in tensorboard and then causing an error. Tried upgrading numpy but that didn’t work. The tensorboard version was upgraded later and it worked. UPDATE: Upgrading the tensorboard can cause other problems, so the above doesn’t work. The root of this problem is the inconsistent versions […]
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STM32F103 Driving LD3320 Speech Recognition Module
STM32F103 Driving LD3320 Speech Recognition Module LD3320 Speech Recognition Module IntroductionModule Pin DefinitionsSTM32F103ZET6 development board and module wiringtest codeResults LD3320 Speech Recognition Module Introduction Based on LD3320, voice recognition/voice control/human-machine dialogue functions can be easily realized in any electronic products, even the simplest system with 51 as the main controller. Add VUI (Voice User Interface) […]
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tensorflow1 tensorflow 2 installation configuration (cpu+gpu) windows+linux new version 2.12+
Installation and deployment of tensorflow 1 and 2 Windows and linux usage is the same, I tested it manually under both win10 and ubuntu2204 This article uses conda’s approach, updated August 17, 2023 Link:tensorflow website Note: If you get an error or get stuck because of network problems, please cancel and try multiple times, I’m […]
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Stable Diffusion tutorial
10,000 Words: Stable Diffusion Nanny Tutorials 2022 is definitely the year of the AI explosion, preceded by thestability.ai expand one’s financial resourcesStable Diffusion model, followed byOpen AI postChatGPTThe two are milestone node event, its importance is no less than when Apple released the iPhone, Google launched Android. they make AI is no longer a remote […]
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NLP Information Extraction Fully Explained: a Practical Guide to PyTorch from Named Entities to Events
catalogs introductoryImportance of context and information extractionObjectives and structure of the article Overview of information extractionWhat is Information ExtractionApplication Scenarios for Information ExtractionKey challenges in information extraction entity identificationWhat is entity identificationApplication Scenarios for Entity RecognitionPyTorch implementation codeInputs, outputs and processes Relational extractionWhat is Relationship ExtractionApplication Scenarios for Relational ExtractionPyTorch implementation codeInputs, outputs and processes […]
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Theory of Convolutional Neural Networks (CNNs)
Study period: 2022.04.10~2022.04.12 Article Catalog 3. Convolutional neural network CNN3.1 Concept of Convolutional Neural Networks3.1.1 What is a CNN?3.1.2 Why use CNNs?3.1.3 Principles of human vision 3.2 Fundamentals of CNN3.2.1 Main structures3.2.2 Convolution layer1. Convolutional operations2. Three modes of convolution3. The nature of convolution 3.2.3 Pooling layer3.2.4 Activation layer3.2.5 Rasterization3.2.6 Full connectivity layer3.2.7 Reverse propagation3.2.8 […]