License Plate Detection and Recognition Using Deep Learning (Pytorch)

License Plate Detection and Recognition Using Deep Learning (Pytorch)

Click on "Xiaobai Learns Vision" above, select to add "Star" or "Top" Heavyweight content delivered first License Plate Recognition Overview License plate recognition based on deep learning, where the vehicle detection network directly uses YOLO for detection. Then, a network is used to detect and recognize the license plate number. The license plate detection network … Read more

Top 10 Deep Learning Models

Top 10 Deep Learning Models

Approximately 10,000 words, recommended reading time: 15 minutes. This article shares the top 10 models in deep learning, which hold significant positions in terms of innovation, application value, and impact. Since the concept of deep learning was proposed in 2006, nearly 20 years have passed. Deep learning, as a revolution in the field of artificial … Read more

General Backbone Networks in Computer Vision

General Backbone Networks in Computer Vision

“Academic Window” is a paper recommendation column launched by the Academic Research Department of the Graduate Affairs Center of the School of Computer Science and Technology, aimed at recommending and sharing the latest academic achievements and classic papers in various fields of computer science to students. In the future, it will be pushed on this … Read more

Network Architecture Design: CNN Based and Transformer Based

Network Architecture Design: CNN Based and Transformer Based

Follow the official account “ML_NLP“ Set as “Starred“, heavy content delivered to you first! Reprinted from | Smarter From DETR to ViT, various works have validated the potential of Transformers in the field of computer vision. Naturally, this raises a new question: which is better for image feature extraction, CNN or Transformer? The advantage of … Read more

A Small Change: CNN Input from Fixed to Variable Image Sizes

A Small Change: CNN Input from Fixed to Variable Image Sizes

Click on the above“Beginner Learning Vision“, select to add “Star” or “Top“ Essential content delivered promptly In this article, we will learn how to classify images of any size without using computationally intensive sliding windows. By modifying the ResNet-18 CNN framework, we will change the required input size from 224×224 to any size. First, we … Read more

The Development of Convolutional Neural Networks and Their Advantages and Disadvantages

The Development of Convolutional Neural Networks and Their Advantages and Disadvantages

Click the above“Beginner Learning Vision” to selectStar or “Pin” Heavyweight content delivered first Introduction In the field of CV, we need to master the most basic knowledge, which is the various architectures of Convolutional Neural Networks (CNNs). Whether we are dealing with image classification, segmentation, object detection, or NLP, we will use the basic CNN … Read more

Interpretation of Attention Mechanisms in Medical Imaging

Interpretation of Attention Mechanisms in Medical Imaging

Click the above“Beginner Learning Vision” and select toStar or “Pin” Important information delivered first time Source|Daniel Liu@Zhihu, https://zhuanlan.zhihu.com/p/138555896 Multi-scale self-guided attention for medical image segmentation The method in this paper is the optimal method for medical image segmentation on the CHAOS MRI Dataset published in 2019, with a final Dice score of 86.75. Introduction: Views … Read more

Research on CNN-BiLSTM Short-term Power Load Forecasting Model Based on Attention Mechanism and ResNet

Research on CNN-BiLSTM Short-term Power Load Forecasting Model Based on Attention Mechanism and ResNet

Research on CNN-BiLSTM Short-term Power Load Forecasting Model Based on Attention Mechanism and ResNet WANG Lize1,2, XIE Dong1,2*, ZHOU Lifeng1,2, WANG Hanqing1,2 (1.School of Civil Engineering, University of South China, Hengyang, Hunan 421001, China;2.Hunan Engineering Laboratory of Building Environmental Control Technology, University of South China, Hengyang, Hunan 421001, China) Abstract:Short term power load forecasting is … Read more

Understanding ResNet: The Essence and Applications of Residual Neural Networks

Understanding ResNet: The Essence and Applications of Residual Neural Networks

This article will cover the essence of ResNetthe principles of ResNetand the applications of ResNet to help you understand Residual Neural Networks (ResNet). Residual Neural Network ResNet 1. The essence of ResNetResNet’s definition: Residual Neural Network (ResNet) is an architecture of deep convolutional neural networks (CNN) that addresses the degradation problem in training deep networks … Read more

New Backbone Network Choice for CNN: HS-ResNet

New Backbone Network Choice for CNN: HS-ResNet

↑ ClickBlue Text Follow the Extreme Market Platform Author丨zzk Source丨GiantPandaCV Editor丨Extreme Market Platform Extreme Market Guide The network structure of this article is manually designed, mainly improving the multi-level division convolution of feature maps, concatenation, which enhances the network’s accuracy while also reducing inference time. It feels like a combination of res2net and ghostnet, and … Read more