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
Modern efficient convolutional neural networks (CNN) always use depthwise separable convolutions (DSC) and neural architecture search (NAS) to reduce the number of parameters and computational complexity. However, they overlook some inherent features of the network. Inspired by visual feature maps and N×N (N>1) convolution kernels, this paper introduces several guidelines to further improve parameter efficiency … Read more
Click on the above “Beginner Learning Vision” to choose to add Star or “Pin” Important content delivered first Many articles on convolutional neural networks explain what CNNs are and their uses, while this article will implement a CNN using C++ and a library called mlpack to classify the MNIST dataset. You may wonder why C++ … 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
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and enterprise researchers. Community Vision is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning at home and abroad, especially for the … 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
Using machine learning for investment has always been a popular subject. In recent years, deep learning models have attracted a lot of attention, especially in the field of computer vision. Therefore, the paper introduced here provides a brand new approach by using the currently hottest computer vision neural network: Convolutional Neural Network (CNN) to predict … 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
Click on "XiaoBai Learns Vision" above, choose to add "Star" or "Top" Heavy content delivered at the first time Introduction This article aims to address overfitting in neural networks. Overfitting will be your main concern as you train the model with only 2000 data samples.There are some methods to help overcome overfitting, namely dropout and … Read more