AliMei’s Guide: ICCV is regarded as one of the top three conferences in the field of computer vision. As one of the highest-level conferences in computer vision, its proceedings represent the latest development directions and levels in the field. Alibaba has multiple papers selected for this year’s conference, and the paper interpreted in this article … Read more
Meng Lei School of Electrical Engineering, Shaanxi University of Technology /Abstract:/ To timely grasp the changes in power load, accurate forecasting is essential. Therefore, a combined model of CNN and LSTM is explored to predict short-term fluctuations in power load from one day to one week. The CNN model is responsible for feature extraction from … Read more
Selected from offconvex Author：John Miller Translated by Machine Heart Contributors: Qianshu, Zhang Qian, Siyuan In recent years, while Recurrent Neural Networks (RNNs) have been dominant, models like autoregressive Wavenet or Transformers are now replacing RNNs in various sequence modeling tasks. Machine Heart has previously introduced RNNs and CNNs for sequence modeling in a GitHub project, … Read more
Selected from MachineLearningMastery Author: Jason Brownlee Translated by Machine Heart Contributors: Nurhachu Null, Lu Xue The encoder-decoder structure has shown advanced levels in several fields, but this structure encodes the input sequence into a fixed-length internal representation. This limits the length of the input sequence and results in poorer performance of the model on particularly … Read more
Author: Huang Yu, Autonomous Driving Scientist Editor: Hoh Xil Source: Huang Yu@Zhihu Produced by: DataFunTalk Note: There is a latest autonomous driving salon at the end of the article, welcome to sign up. Introduction: Deep learning has been “hot” for more than ten years since 2006, and the most common applications we see are in … Read more
Follow the public account “ML_NLP“ Set as “Starred“, delivering heavyweight content to you first! Reprinted from | PaperWeekly ©PaperWeekly Original · Author｜Su Jianlin Unit｜Zhuiyi Technology Research Direction｜NLP, Neural Networks Although Transformer models have conquered most fields in NLP, RNN models like LSTM and GRU still hold unique value in certain scenarios, making it worthwhile for … Read more
Author | Sandeep Bhupatiraju Translator | Liu Zhiyong Editor | Debra Chen AI Frontline Overview: Over a century ago, in the United States, people used Morse code to send the first telegram in human history, opening a new chapter for mankind. The advent of Morse code has had a profound and far-reaching impact on human … Read more
Author | Bill Vorhies Translator | Gai Lei Editor | Vincent AI Frontline Overview: From some interesting use cases, it seems we can completely combine CNN and RNN/LSTM. Many researchers are currently working on this research. However, the latest research trends in CNN may render this idea outdated. For more quality content, please follow the … Read more
In an era flooded with fragmented reading, fewer people pay attention to the exploration and thinking behind each paper. In this column, you will quickly get the highlights and pain points of selected papers, keeping up with the forefront of AI achievements. Click the “Read Original” at the bottom of this article to join the … Read more
Broadly speaking, NN (or the more elegant DNN) can indeed be considered to encompass specific variants like CNN and RNN. In practical applications, the so-called deep neural network DNN often integrates various known structures, including convolutional layers or LSTM units. However, based on the question posed, the DNN here should specifically refer to a fully … Read more