Deep learning for smart manufacturing: Methods and applications

阿新 • • 發佈：2018-12-28

Smart manufacturing refers to using advanced data analytics to complement physical science for improving system performance and decision making. With the widespread deployment of sensors and Internet of Things, there is an increasing need of handling big manufacturing data characterized by high volume, high velocity, and high variety. Deep learning provides advanced analytics tools for processing and analysing big manufacturing data. This paper presents a comprehensive survey of commonly used deep learning algorithms and discusses their applications toward making manufacturing "smart". The evolvement of deep learning technologies and their advantages over traditional machine learning are firstly discussed.

Deep learning for smart manufacturing: Methods and applications

Smart manufacturing refers to using advanced data analytics to complement physical science for improving system performance and decision making. With the w

《Transform- and multi-domain deep learning for single-frame rapid autofocusing》筆記

作者的快速聚焦方法是使用卷積網路從單個成像圖片中預測圖片的離焦距。之前的聚焦方法大多需要測量多張成像圖片的聚焦值來預測聚焦鏡頭的移動方向和移動距離，但是論文的方法可以直接預測出聚焦位置的方向和距離。作者使用不同的圖片特徵，包括圖片的空間域特徵、頻域特徵、自相

Deep Learning for Robotics 資源匯總

theano .text tor tro org () -c 四軸 parent 1 前言在最新Nature的Machine Intelligence 中Lecun。Hinton和Bengio三位大牛的Review文章Deep Learning中。最

最實用的深度學習教程 Practical Deep Learning For Coders (Kaggle 冠軍 Jeremy Howard 親授)

ted del src learning over attention wid multi 美國 Jeremy Howard 在業界可謂大名鼎鼎。他是大數據競賽平臺 Kaggle 的前主席和首席科學家。他本人還是 Kaggle 的冠軍選手。他是美國奇點大學（Singular

論文筆記-Wide & Deep Learning for Recommender Systems

wiki body pos ear recommend sys con 損失函數 wrapper 本文提出的W&D是針對rank環節的模型。網絡結構：本文提出的W&D是針對rank環節的模型。網絡結構： wide是簡單的線性模型，但

Python計算機視覺深度學習三合一Deep learning for computer vision with Python高清pdf

Deep Learning for Computer Vision with Python Starter Bundle pdf Deep Learning for Computer Vision with Python Practitioner Bundle pdf Deep Learning for

「Deep Learning」Notes on Squeeze-and-Excitation Network (SENet)

QQ Group: 428014259 Sina Weibo：小鋒子Shawn Tencent E-mail：[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/84179554 [1]

「Deep Learning」Note on Gather and Excite Network (GENet)

QQ Group: 428014259 Sina Weibo：小鋒子Shawn Tencent E-mail：[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/84179196 SEN

「Computer Vision」Notes on Deep Learning for Generic Object Detection

QQ Group: 428014259 Sina Weibo：小鋒子Shawn Tencent E-mail：[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/83834249 [1]

Deep Learning for Generic Object Detection: A Survey

Abstract 通用物件檢測，旨在從自然影象中的大量預定義類別定位物件物體，是計算機視覺中最基本和最具挑戰性的問題之一。近幾年來，深度學習技術成為了直接從資料中學習特徵表示的有力方法，並在通用物件檢測領域取得了顯著的突破。鑑於這個快速發展的時代，本文的目標是對深度學習

Deep Learning for Recommender Systems資料

基於深度學習的推薦系統的論文（包括論文程式碼 PPT） https://handong1587.github.io/deep_learning/2015/10/09/recommendation-system.html https://github.com/robi56/Deep-

Week1.3 Simple deep learning for text classification

Neural networks for words（and characters) 在本節中我們將學習如何將神經網路用於文字分類，還將學習卷積神經網路相關的原理. 回顧–Bag of words way 在前面課程中，我們學習瞭如何將一段文本當作一系列word

Deep Learning for Generic Object Detection: A Survey 閱讀筆記

目錄摘要 1.介紹 2.背景 2.1問題 3.框架摘要目標監測旨在從自然影象中定位出大量預定義類別的例項物件，是機器視覺中最基本也是最具挑戰的問題。近年來，深度學習技術作為直接從資料學習特徵表示的強

USING DEEP LEARNING FOR ANOMALY DETECTION IN RADIOLOGICAL IMAGES

關注Deep Learning在醫療資料中的應用，指出了Deep Learning在醫療資料應用中遇到的問題，即不能像處理圖片資料那樣，輸入大量訓練資料，而是相對資料量的缺乏；注意到人類的學習過程，當教小孩讀和寫的時候，它是一個學生和老師互動反饋的過程，受此啟發

Deep Learning for Generic Object Detection: A Survey -- 目標檢測綜述總結

最近，中國國防科技大學、芬蘭奧盧大學、澳大利亞悉尼大學、中國香港中文大學和加拿大滑鐵盧大學等人推出一篇最新目標檢測綜述，詳細闡述了當前目標檢測最新成就和關鍵技術。文章最後總結了未來8個比較有前景的方向，對學習目標檢測的人員提供了很大的幫助，在此翻譯這篇文章，方便

Unsupervised deep learning for data interpolation

Ideally if training data with reference is available we could train the network to reconstruct missing values by comparing reconstruction to the target. Bu

Deep Learning for Natural Language Processing Archives

Machine translation is the challenging task of converting text from a source language into coherent and matching text in a target language. Neural machine

Deep Learning for Time Series Archives

Human activity recognition is the problem of classifying sequences of accelerometer data recorded by specialized harnesses or smart phones into known well

Competitive Advantages of Deep Learning for Your Business

What do you think of when you hear about AI? Do you picture your favourite sci-fi movie or a book that you read when you were younger? In that favourite bo

MIT Deploys Deep Learning for Analyzing Mammograms

Depending on which radiologist analyzes a mammogram, there’s a huge variation in breast density readings — an assessment that indicates a patient’s risk fo