Tags
Language
Tags
<<
April 2024
Su Mo Tu We Th Fr Sa
31 1 2 3 4 5 6
7 8 9 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 30 1 2 3 4
  1. Home
  2. eBooks & eLearning
  3. Principal component analysis
https://canv.ai/
The picture is generated by canv.ai

We are excited to announce that Canv.ai now features a built-in translator, allowing you to communicate in your native language. You can write prompts in your language, and they will be automatically translated into English, facilitating communication and the exchange of ideas!

We value freedom of speech and guarantee the absence of censorship on Canv.ai. At the same time, we hope and believe in the high moral standards of our users, which will help maintain a respectful and constructive atmosphere.

👉 Check for yourself!

Five-Layer Intelligence of the Machine Brain: System Modelling and Simulation

Posted By: AvaxGenius
Date: 17 Jun 2022 22:19:53
Five-Layer Intelligence of the Machine Brain: System Modelling and Simulation

Five-Layer Intelligence of the Machine Brain: System Modelling and Simulation by Wen-Feng Wang
English | EPUB | 2022 | 223 Pages | ISBN : 9811902712 | 35.5 MB

This book intends to report the new results of the efforts on the study of Layered Intelligence of the Machine Brain (LIMB). The book collects novel research ideas in LIMB and summarizes the current machine intelligence level as “five layer intelligence”- environments sensing, active learning, cognitive computing, intelligent decision making and automatized execution. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms, and applications of LIMB.
Details

Generalized Principal Component Analysis (Repost)

Posted By: AvaxGenius
Date: 7 May 2020 19:03:54
Generalized Principal Component Analysis (Repost)

Generalized Principal Component Analysis by René Vidal
English | PDF,EPUB | 2016 | 590 Pages | ISBN : 0387878106 | 23.1 MB

This book provides a comprehensive introduction to the latest advances in the mathematical theory and computational tools for modeling high-dimensional data drawn from one or multiple low-dimensional subspaces (or manifolds) and potentially corrupted by noise, gross errors, or outliers. This challenging task requires the development of new algebraic, geometric, statistical, and computational methods for efficient and robust estimation and segmentation of one or multiple subspaces. The book also presents interesting real-world applications of these new methods in image processing, image and video segmentation, face recognition and clustering, and hybrid system identification etc.
Details
UPWARDS