Fundamentals of Neural Networks

Fundamentals of Neural Networks

(Click the public account above, you can quickly follow) Source: Poll’s Notes cnblogs.com/maybe2030/p/5597716.html If you have good articles to submit, please click → here for details Table of Contents 1. Neuron Model 2. Perceptron and Neural Networks 3. Backpropagation Algorithm 4. Common Neural Network Models 5. Deep Learning 6. References Currently, deep learning (Deep Learning, … Read more

Tesla Executive Reveals Autonomous Driving Technology: 48 Neural Networks in Action, Detecting Up to 1000 Objects

Tesla Executive Reveals Autonomous Driving Technology: 48 Neural Networks in Action, Detecting Up to 1000 Objects

How Does Tesla Achieve City Autonomous Driving with Cameras? Written by | James Recently, Tesla updated its autonomous driving software to version 2020.12, which includes the automatic recognition of traffic lights and stop signs. If Tesla is equipped with the FSD full self-driving capability package, it can experience the autonomous driving feature of stopping at … Read more

Understanding Deep Learning: Basics of Artificial Neural Networks

Understanding Deep Learning: Basics of Artificial Neural Networks

Reprinted from Yunqi Community as required ID: yunqiinsight Author | doflamingo Introduction I have touched on deep learning during my studies, but only superficially. In this era of data and algorithms, it is necessary to get closer to the algorithms. Therefore, from the perspective of an engineer, I hope to record the basics of deep … Read more

CVPR 2023: New Network Cloning Technology Proposed by LV Lab

CVPR 2023: New Network Cloning Technology Proposed by LV Lab

Machine Heart Report Editor: Wang Qiang What happens when neural networks reach 100%? What is the ultimate form of neural networks? What is a network superbody? The answers to these questions may be found in the movie “Lucy”. In the movie, as the protagonist Lucy gradually develops her brain power, she gains the following abilities: … Read more

Optical Illusions: Blind Spots of Neural Networks

Optical Illusions: Blind Spots of Neural Networks

Click the image for details↑ Human vision is an extraordinary ability. Although it has evolved over millions of years in specific environments, it can accomplish tasks that early visual systems have never experienced. Reading is a great example, such as recognizing cars, airplanes, road signs, and other man-made objects. However, the visual system also has … Read more

Automated Quantum Neural Network Search

Automated Quantum Neural Network Search

As the next generation of advanced computing technology, quantum computers are on the brink of practical application. A landmark milestone was Google’s demonstration of quantum supremacy in 2019 using a 54-qubit superconducting quantum processor [1]. Since then, how to utilize quantum computing devices to solve real-world problems and achieve performance surpassing classical computers under existing … Read more

Deep Painterly Harmonization: Merging Art with AI

Deep Painterly Harmonization: Merging Art with AI

Li Zi from A Fei Si Quantum Bit | WeChat Official Account QbitAI ”Master, can you help me Photoshop my face onto the model in the street photo? Oh right, not just that, it has to look like the model…” Extracting an element from one photo and seamlessly blending it into another seems like a … Read more

Exploding the Machine Learning Circle: New Activation Function SELU Introduced

Exploding the Machine Learning Circle: New Activation Function SELU Introduced

Selected from arXiv Compiled by Machine Heart Contributors: Jiang Siyuan, Smith, Li Yazhou Recently, a paper titled “Self-Normalizing Neural Networks” published on arXiv has garnered significant attention in the community. It introduces the Scaled Exponential Linear Unit (SELU), which brings in a self-normalizing property. This unit mainly uses a function g to map the mean … Read more

Comprehensive Survey on Neuromorphic Computing and Neural Network Hardware: From Research Overview to Future Prospects

Comprehensive Survey on Neuromorphic Computing and Neural Network Hardware: From Research Overview to Future Prospects

Selected from arXiv Compiled by Machine Heart Contributors: Jane W, Wu Pan Neuromorphic computing is considered an important direction for future artificial intelligence computing. Recently, several researchers from the Institute of Electrical and Electronics Engineers (IEEE) jointly published an 88-page overview paper that comprehensively reviews the development of neuromorphic computing over the past 35 years … Read more

New Approach to Neural Networks: OpenAI Solves Nonlinear Problems with Linear Networks

New Approach to Neural Networks: OpenAI Solves Nonlinear Problems with Linear Networks

Selected by OpenAI Author: JAKOB FOERSTER Translation by Machine Heart Using linear networks for nonlinear computation is an unconventional approach. Recently, OpenAI published a blog introducing their new research on deep linear networks, which do not use activation functions, yet achieve 99% training accuracy and 96.7% testing accuracy on MNIST. This new research has reignited … Read more