“Contribute to Make in India Program” 35 MM F-MOUNT MACHINE VISION LENS BMT-35F18MP Version: V1.1-MAY-2016 Key Highlights

Source URL: www.balaji-microtechnologies.com

Frankenstein: Learning Deep Face Representations using Small Data Guosheng Hu, Xiaojiang Peng, Yongxin Yang, Timothy Hospedales, Jakob Verbeek To cite this version:

Source URL: hal.inria.fr

• Artificial intelligence
• Learning
• Machine learning
• Computational neuroscience
• Applied mathematics
• Face recognition
• Artificial neural networks
• Computer vision
• Deep learning
• Convolutional neural network
• Eigenface
• Facial recognition system

Microsoft PowerPoint - cs559f15_Week5.pptx

Source URL: www.cs.stevens.edu

• Computer vision
• Artificial intelligence
• Vision
• Multivariate statistics
• Face recognition
• Machine learning
• California Institute of Technology
• Caltech 101
• Eigenface
• MNIST database
• Principal component analysis
• Data set

arXiv:1604.03755v1 [cs.CV] 13 AprVConv-DAE: Deep Volumetric Shape Learning Without Object Labels Abhishek Sharma1 , Oliver Grau2 , Mario Fritz3 1

Source URL: arxiv.org

• Artificial neural networks
• Imaging
• 3D computer graphics
• Artificial intelligence
• Vision
• Computational neuroscience
• 3D imaging
• Deep learning
• Machine learning
• Convolutional neural network
• Voxel
• Feature learning

http://www.mva-org.jp/ MVA2017 IAPR INTERNATIONAL CONFERENCE ON MACHINE VISION APPLICATIONS Sponsors: MVA Organization, IAPR and Graduate School of Information Science, Nagoya University

Source URL: www.mva-org.jp

Psy 392: Robot & Human Vision. SpringTu, Th: 3-4:15PM BLDG: Psyc, Rm. 277 Instructor: Z. Pizlo () Text: Pizlo et alMaking a machine that sees like us. Oxford University Press. Electronic

Source URL: www1.psych.purdue.edu

MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, JapanHigher-Dimensional Segmentation by Minimum-cut Algorithm Hiroshi Ishikawa Department of Information & Biological

Source URL: b2.cvl.iis.u-tokyo.ac.jp

CS 558: Homework Assignment 4 - Visual Recognition Due: April 26, 11:59pm Philippos Mordohai Department of Computer Science Stevens Institute of Technology

Source URL: www.cs.stevens.edu

• Artificial intelligence
• Image processing
• Statistics
• Nonparametric statistics
• Feature detection
• Vision
• Computer vision
• Machine learning
• K-nearest neighbors algorithm
• Image histogram
• Statistical classification
• Histogram

Class Generative Models based on Feature Regression for Pose Estimation of Object Categories Michele Fenzi, Laura Leal-Taixé, Bodo Rosenhahn, Jörn Ostermann Institute for Information Processing (TNT), Leibniz Universit

Source URL: www.tnt.uni-hannover.de

• Artificial intelligence
• Statistics
• Computer vision
• Robot control
• Econometrics
• Machine learning
• 3D single-object recognition
• Outline of object recognition
• Pose
• Cross-validation
• Regression analysis

Recognizing Actions from Still Images Nazli Ikizler, R. Gokberk Cinbis, Selen Pehlivan and Pinar Duygulu Bilkent University, Dept of Computer Engineering, 06800, Ankara, Turkey {inazli, cinbis, pselen, duygulu}@bilkent.e

Source URL: web.cs.hacettepe.edu.tr

• Formal sciences
• Artificial intelligence
• Science and technology
• Vision
• Image processing
• Computational neuroscience
• Machine learning
• Feature detection
• Histogram of oriented gradients
• Outline of object recognition
• Conference on Computer Vision and Pattern Recognition
• Computer vision