Click the above “Beginner Learning Vision” to choose to add “Starred” or “Pinned“ Important content delivered at the first time The Essence of Convolution Conventional Convolution Single-channel Convolution Multi-channel Convolution 3D Convolution Transposed Convolution 1×1 Convolution Depthwise Separable Convolution Dilated Convolution The Essence of Convolution Before introducing various convolutions, it is necessary to revisit the … Read more
Are you a new friend? Remember to click the blue text to follow me~ The official account has changed its push rules, remember to click “Looking” after reading~ Next time a new article will appear in your subscription list in a timely manner Author | Captain Note | The official account is responsible for pushing … Read more
Click on the "Xiaobai Learns Vision" above, select "Star" or "Top" Heavyweight content delivered first time Here, we will discuss the detection of crop disease severity using OpenCV image processing techniques. This process does not involve any training part. Based on color segmentation technology, we only extract healthier plant areas and calculate disease severity based … Read more
In today’s digital age, Convolutional Neural Networks (CNNs), as a subset of Deep Learning (DL), are widely used in various computer vision tasks such as image classification, object detection, and image segmentation. Many types of CNNs have been designed to meet specific needs and requirements, including one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) CNNs, as … Read more
About 3400 words, recommended reading time: 10+ minutes This article will comprehensively introduce the attention mechanism in CNNs, from basic concepts to practical implementations, providing readers with in-depth understanding and practical guidance. The attention mechanism has become an indispensable component of deep learning models, especially in Convolutional Neural Networks (CNNs). By enabling models to selectively … Read more
Click the above “Beginner Learning Vision“, choose to add “Starred” or “Pinned“ Heavyweight content delivered at the first time Convolutional Neural Networks (CNNs) have achieved unprecedented success in the field of computer vision, but we currently do not have a comprehensive understanding of the reasons for their remarkable effectiveness. In March 2018, Isma Hadji and … Read more
Source: Original article by CSDN blogger “Fate_fjh”. The traditional CNN network can only provide the LABEL of an image, but in many cases, it is necessary to segment the identified objects to achieve end to end recognition. This is where FCN comes in, providing a very important solution for object segmentation, with the core being … Read more
Click the above “Beginner’s Guide to Vision“, select to add “Starred” or “Pinned“ Important content delivered promptly This article is reprinted from: OpenCV Academy Traditional Object Recognition – Pattern Recognition Traditional pattern recognition neural network (NN) algorithms are based on gradient descent and learn to recognize and classify different target samples based on a large … Read more
This article shares an analysis of the mathematical principles of CNNs, which will help you deepen your understanding of how neural networks work in CNNs. As a recommendation, this article will include quite complex mathematical equations; if you are not familiar with linear algebra and calculus, that’s okay. The goal is not to memorize these … Read more
Hello everyone, today we will talk about CNN. In simple terms, Convolutional Neural Networks (CNNs) are deep learning models particularly suited for processing image data. CNN consists of multiple layers of neural networks, each performing specific processing on the input data, ultimately outputting a classification result or other objectives. Imagine you are looking at an … Read more