Source: Deephub Imba This article contains approximately 3000 words, and is suggested to be read in 5 minutes This article will introduce the application of CNN to solve simple 2D path planning problems. Convolutional Neural Networks (CNN) are popular models for tasks such as image classification, segmentation, and object detection. This article applies CNN to … 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
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first! Author: Justin Ho Editor: Xixiaoyao’s Cute Shop Source: https://zhuanlan.zhihu.com/p/28749411 Introduction The CNN has evolved from AlexNet in 2012 to various CNN models invented by scientists, each deeper, more accurate, and lighter than the last. Below, we will briefly review some revolutionary works in … Read more
Most existing commercial ECG analysis systems are often based on rule-based algorithms as disease-specific ECG diagnostic standards. Research indicates that machine learning can effectively recognize ECG diagnoses from a set of labeled data. This data-driven learning analysis can serve as a powerful supplement to existing automated ECG algorithms and can establish a new ECG diagnostic … Read more
In today's era, machines have successfully achieved 99% accuracy in understanding and recognizing features and objects in images. We see this every day – smartphones can recognize faces in the camera; the ability to search for specific photos using Google Image Search; scanning text from barcodes or books. All of this is made possible by … Read more
This article is authorized for reprint by AI new media Quantum Bit, please contact the source for reprinting. This article is about 2000 words, and it is recommended to read in 5 minutes. When it comes to image classification, challenges arise from large images, varying shapes and positions of objects, which poses difficulties for ordinary … Read more
Click on 'Xiaobai Learns Vision' above, select 'Star' or 'Top' to receive important content first. Author | yishun@Zhihu Source丨https://zhuanlan.zhihu.com/p/53683453 Editor | Jishi Platform Introduction Visual analysis of neural networks is significant for both learning and practical applications. Based on this, this article introduces three visualization methods for CNNs: visualizing intermediate feature maps, visualizing convolutional kernels, … Read more
Click on the above “Beginner Learning Visuals”, choose to add “Star” or “Top” Heavyweight content delivered first time From a high-level perspective of our deep learning project, we have prepared the data, and now we are ready to build our model. Prepare Data Build Model Train Model Analyze Model Results When we refer to the … Read more
Madio.net Mathematics China Reprinted from:Author丨Mountain and Water You and Me @ Zhihu Source丨https://zhuanlan.zhihu.com/p/468100301 Editor丨Extreme City Platform Currently, building a Convolutional Neural Network (CNN) is generally done directly using deep learning frameworks such as Pytorch or Tensorflow, which is quite simple. However, if you’re writing the backpropagation process from scratch, it is much more complicated than … Read more
Author: Nan Ke Yi Meng Ning Chen Lun @ Zhihu (Authorized) Editor: Jishi Platform Source: https://zhuanlan.zhihu.com/p/61898234 The mathematical derivation of backpropagation in multilayer perceptrons is mainly represented using mathematical formulas. In fully connected neural networks, these are not complicated, and even purely mathematical formulas are relatively easy to understand.However, convolutional neural networks are relatively more … Read more