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
The Ancient and Modern Medical Case Cloud Platform Providing over 400,000 ancient and modern medical case retrieval services Supports manual, voice, OCR, and batch structured entry of medical cases Designed with nine major analysis modules, closely aligned with clinical needs Supports collaborative analysis of massive medical cases and personal cases on the platform Cloud Medical … Read more
Click the blue text above to follow ↑↑↑↑↑ Author: Andrey Kurenkov As the puzzle of training multi-layer neural networks is unraveled, this topic has once again become extraordinarily popular, and Rosenblatt’s lofty ambitions seem to be realized. Until 1989, another key discovery was published, which is still widely cited in textbooks and major lectures. Multi-layer … Read more
Source: Machine Vision Knowledge Recommender This article is approximately 11,000 words long and is recommended for a reading time of 10+ minutes. This article will introduce deep learning technology, neural networks, convolutional neural networks, and their applications in related fields. In today’s internet era, the intricate big data and network environment pose significant challenges to … Read more
Click the above“Beginner Learn Vision”, choose to addStar or “Top” Important content delivered in real-time The first convolutional neural network was proposed by Alexander Waibel in 1987, known as the Time Delay Neural Network (TDNN) [5]. TDNN is a convolutional neural network applied to speech recognition problems. It uses FFT to preprocess speech signals as … Read more
Source: Machine Learning Algorithms This article is about 5000 words long, and it is recommended to read in 8 minutes This article summarizes some basic concepts about Convolutional Neural Networks (CNN). Introduction This article summarizes some basic concepts about Convolutional Neural Networks (CNN) and provides detailed explanations of the principles involved. Through this article, one … Read more
Original Title | Gentle Dive into Math Behind Convolutional Neural Networks
In today’s internet age, the intricate big data and network environment pose significant challenges to traditional information processing theories, artificial intelligence, and artificial neural networks.In recent years, deep learning has gradually come into people’s view, with an increasing number of cases solving various problems through deep learning.Some traditional image processing techniques can also achieve superior … Read more
Selected from Medium Translated by Machine Heart Contributors: Lu Xue, Li Zenan Not long ago, Andrew Ng’s fourth course on Convolutional Neural Networks was released on Coursera. This article is a reflection written by Ryan Shrott, Chief Analyst at the National Bank of Canada, after completing the course, which helps everyone intuitively understand and learn … Read more
Click on the "Xiaobai Learns Vision" above, choose to add "Starred" or "Pinned" Heavyweight content delivered at the first time Introduction MoD is a new method for Convolutional Neural Networks (CNNs) that improves computational efficiency by selectively processing channels. Unlike traditional static pruning methods, MoD adopts a dynamic computation approach, adjusting computational resources based on … Read more