Tag:deep learning
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Opencv Image Processing
Article Catalog Blogger’s Boutique Column NavigationNote: The following source code can be run, different projects involved in the function are analyzed in detail.11、Image project practice(i) Bank card number identification — sort_contours(), resize()(ii) document scanning OCR recognition — cv2.getPerspectiveTransform() + cv2.warpPerspective(), np.argmin(), np.argmax(), np.diff()detectAndDescribe(), matchKeypoints(), cv2.findHomography(), cv2.warpPerspective(), drawMatches()(iv) Parking lot space detection (Keras-based CNN classification) — […]
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YOLOv5 – Explanation of the project directory structure
preamble The previous section briefly describes the network structure and innovations of YOLOv5 (the drive-through:[YOLO Series] YOLOv5 Super Detailed Explanation (Network Detailed Explanation)) In the next step we will go into a deeper study of YOLOv5, starting with the source code interpretation. Because I am a pure white, just started to download the source code […]
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OpenCV meets deep learning
OpenCV in action (33) – OpenCV meets deep learning 0. Preface 1. Deep learning and convolutional neural networks 2. Face detection using deep learning 2.1 Introduction to SSDs 2.2 Performing Face Detection Using SSDs 3. Complete code wrap-up 0. Preface Deep learning is a subfield of machine learning, based on traditional neural networks and convolutional […]
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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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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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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 […]
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Anchor based and Anchor free
Difference between anchor-free and anchor-based Anchor-free and anchor-based are two different target detection methods, the difference being whether or not a predefined anchor box is used to match a real target box. Anchor-based methods use anchor boxes of different sizes and shapes to regress and categorize targets, such as faster rcnn, retinanet, and yolo, etc. […]
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Example of constructing a neural network
Article Catalog neural network1. Import of relevant libraries2. Defining a layer3. Construction of data sets4. Defining the basic model5. Variable initialization6. Commencement of training P.S. Series of articles neural network A neural network is a bionic machine learning algorithm inspired by the nervous system of the human brain. It consists of multiple neurons (or nodes) […]
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Logistic regression done with TensorFlow
Article Catalog Logistic regression done with TensorFlow1. Environmental settings2. Data reading3. Prepare the placeholder4. Prepare parameters/weights5. Compute the loss function of multiclassified softmax6. Prepare the optimizer7. Perform the operations defined in the graph in the session. P.S. Series of articles Logistic regression done with TensorFlow TensorFlow is an open source machine learning framework developed by […]