Enviar pesquisa
Carregar
A bayesian framework for unsupervised one-shot learning of object categories
•
9 gostaram
•
2,282 visualizações
W
wolf
Seguir
Li Fei fei, Rob Fergus, Pietro Perona
Leia menos
Leia mais
Tecnologia
Educação
Denunciar
Compartilhar
Denunciar
Compartilhar
1 de 32
Recomendados
SNLI_presentation_2
SNLI_presentation_2
Viral Gupta
Session 21
Session 21
butest
Robust Audio Adversarial Example for a Physical Attack
Robust Audio Adversarial Example for a Physical Attack
Hiromu Yakura
One-Shot Learning
One-Shot Learning
Jisung Kim
Matching networks for one shot learning
Matching networks for one shot learning
Kazuki Fujikawa
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...
남주 김
NIPS読み会2013: One-shot learning by inverting a compositional causal process
NIPS読み会2013: One-shot learning by inverting a compositional causal process
nozyh
論文紹介 Semi-supervised Learning with Deep Generative Models
論文紹介 Semi-supervised Learning with Deep Generative Models
Seiya Tokui
Mais conteúdo relacionado
Destaque
Generative adversarial networks
Generative adversarial networks
남주 김
Normas De Corriente Alterna Y Directa
Normas De Corriente Alterna Y Directa
lalocm
Situación de las instalaciones eléctricas en México
Situación de las instalaciones eléctricas en México
Efren Franco
Metodos de la arquitectura y arq contemporanea
Metodos de la arquitectura y arq contemporanea
Diana Laura Cue Rodriguez
How to go from structureless to structured without losing your vibe
How to go from structureless to structured without losing your vibe
Camille Fournier
From Conventional Machine Learning to Deep Learning and Beyond.pptx
From Conventional Machine Learning to Deep Learning and Beyond.pptx
Chun-Hao Chang
Centreofgravityandstabilitystuver 100518122326-phpapp02
Centreofgravityandstabilitystuver 100518122326-phpapp02
Rusya Yahaya
Introduction to Digital Journalism
Introduction to Digital Journalism
Gokul Alex
(DL輪読)Matching Networks for One Shot Learning
(DL輪読)Matching Networks for One Shot Learning
Masahiro Suzuki
Learning to remember rare events
Learning to remember rare events
홍배 김
The Art Of Practicing - WebSummit 2014
The Art Of Practicing - WebSummit 2014
Nikolai Onken
Design For Society
Design For Society
Changeist
PresentacióN Corriente Alterna Y Continua
PresentacióN Corriente Alterna Y Continua
tecfabiancho
InfoGAN: Interpretable Representation Learning by Information Maximizing Gene...
InfoGAN: Interpretable Representation Learning by Information Maximizing Gene...
홍배 김
Convolutional Neural Network (CNN) presentation from theory to code in Theano
Convolutional Neural Network (CNN) presentation from theory to code in Theano
Seongwon Hwang
Convolutional neural network in practice
Convolutional neural network in practice
남주 김
Interaction Networks for Learning about Objects, Relations and Physics
Interaction Networks for Learning about Objects, Relations and Physics
Ken Kuroki
Normalization 방법
Normalization 방법
홍배 김
Electricidad
Electricidad
sandra maestre
Design Physics
Design Physics
Gokul Alex
Destaque
(20)
Generative adversarial networks
Generative adversarial networks
Normas De Corriente Alterna Y Directa
Normas De Corriente Alterna Y Directa
Situación de las instalaciones eléctricas en México
Situación de las instalaciones eléctricas en México
Metodos de la arquitectura y arq contemporanea
Metodos de la arquitectura y arq contemporanea
How to go from structureless to structured without losing your vibe
How to go from structureless to structured without losing your vibe
From Conventional Machine Learning to Deep Learning and Beyond.pptx
From Conventional Machine Learning to Deep Learning and Beyond.pptx
Centreofgravityandstabilitystuver 100518122326-phpapp02
Centreofgravityandstabilitystuver 100518122326-phpapp02
Introduction to Digital Journalism
Introduction to Digital Journalism
(DL輪読)Matching Networks for One Shot Learning
(DL輪読)Matching Networks for One Shot Learning
Learning to remember rare events
Learning to remember rare events
The Art Of Practicing - WebSummit 2014
The Art Of Practicing - WebSummit 2014
Design For Society
Design For Society
PresentacióN Corriente Alterna Y Continua
PresentacióN Corriente Alterna Y Continua
InfoGAN: Interpretable Representation Learning by Information Maximizing Gene...
InfoGAN: Interpretable Representation Learning by Information Maximizing Gene...
Convolutional Neural Network (CNN) presentation from theory to code in Theano
Convolutional Neural Network (CNN) presentation from theory to code in Theano
Convolutional neural network in practice
Convolutional neural network in practice
Interaction Networks for Learning about Objects, Relations and Physics
Interaction Networks for Learning about Objects, Relations and Physics
Normalization 방법
Normalization 방법
Electricidad
Electricidad
Design Physics
Design Physics
Mais de wolf
Eigenfaces and Fisherfaces
Eigenfaces and Fisherfaces
wolf
Shai Avidan's Support vector tracking and ensemble tracking
Shai Avidan's Support vector tracking and ensemble tracking
wolf
Constellation Models and Unsupervised Learning for Object Class Recognition
Constellation Models and Unsupervised Learning for Object Class Recognition
wolf
PCA-SIFT: A More Distinctive Representation for Local Image Descriptors
PCA-SIFT: A More Distinctive Representation for Local Image Descriptors
wolf
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Fe...
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Fe...
wolf
Recovering 3D human body configurations using shape contexts
Recovering 3D human body configurations using shape contexts
wolf
Rafi Zachut's slides on class specific segmentation
Rafi Zachut's slides on class specific segmentation
wolf
Avihu Efrat's Viola and Jones face detection slides
Avihu Efrat's Viola and Jones face detection slides
wolf
Ala Stolpnik's Standard Model talk
Ala Stolpnik's Standard Model talk
wolf
Michal Erel's SIFT presentation
Michal Erel's SIFT presentation
wolf
Gil Shapira's Active Appearance Model slides
Gil Shapira's Active Appearance Model slides
wolf
Moshe Guttmann's slides on eigenface
Moshe Guttmann's slides on eigenface
wolf
Object recognition seminar S2006E01
Object recognition seminar S2006E01
wolf
Mais de wolf
(13)
Eigenfaces and Fisherfaces
Eigenfaces and Fisherfaces
Shai Avidan's Support vector tracking and ensemble tracking
Shai Avidan's Support vector tracking and ensemble tracking
Constellation Models and Unsupervised Learning for Object Class Recognition
Constellation Models and Unsupervised Learning for Object Class Recognition
PCA-SIFT: A More Distinctive Representation for Local Image Descriptors
PCA-SIFT: A More Distinctive Representation for Local Image Descriptors
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Fe...
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Fe...
Recovering 3D human body configurations using shape contexts
Recovering 3D human body configurations using shape contexts
Rafi Zachut's slides on class specific segmentation
Rafi Zachut's slides on class specific segmentation
Avihu Efrat's Viola and Jones face detection slides
Avihu Efrat's Viola and Jones face detection slides
Ala Stolpnik's Standard Model talk
Ala Stolpnik's Standard Model talk
Michal Erel's SIFT presentation
Michal Erel's SIFT presentation
Gil Shapira's Active Appearance Model slides
Gil Shapira's Active Appearance Model slides
Moshe Guttmann's slides on eigenface
Moshe Guttmann's slides on eigenface
Object recognition seminar S2006E01
Object recognition seminar S2006E01
Último
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1
DianaGray10
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )
Brian Pichman
UiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation Developers
UiPathCommunity
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
Daniel Santiago Silva Capera
Designing A Time bound resource download URL
Designing A Time bound resource download URL
Runcy Oommen
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptx
Udaiappa Ramachandran
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.
YounusS2
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
infogdgmi
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
Matt Ray
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Safe Software
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
DianaGray10
Salesforce Miami User Group Event - 1st Quarter 2024
Salesforce Miami User Group Event - 1st Quarter 2024
SkyPlanner
20150722 - AGV
20150722 - AGV
Jamie (Taka) Wang
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
D Cloud Solutions
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7
DianaGray10
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBX
Tarek Kalaji
9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team
Adam Moalla
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership Blueprint
Mahmoud Rabie
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
shyamraj55
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?
IES VE
Último
(20)
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )
UiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation Developers
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
Designing A Time bound resource download URL
Designing A Time bound resource download URL
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptx
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
Salesforce Miami User Group Event - 1st Quarter 2024
Salesforce Miami User Group Event - 1st Quarter 2024
20150722 - AGV
20150722 - AGV
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBX
9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership Blueprint
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?
A bayesian framework for unsupervised one-shot learning of object categories
1.
2.
Slides Credit: Gary
Bradski, Sebastian Thrun, Rob Fergus, Pietro Perona, Andrew Zisserman, Li Fei-Fei, Antonio Torralba
3.
This guy is
wearing a haircut called a “Mullet”
4.
Find the Mullets…
One-Shot Learning
5.
~10,000 to 30,000
6.
7.
8.
9.
10.
11.
12.
13.
Posterior (Same family
as Prior) Likelihood Prior (conjugate to the likelihood)
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
Performance Results –
Face Model 1 training image 5 training images
25.
26.
Performance Results –
Motorbikes 1 training image 5 training images
27.
28.
29.
Prior Hyper-Parameters
30.
Results Comparison 8
–15 % < 1 min 1 ~ 5 Bayesian One-Shot 5.6 -10 % Hours 200~400 Burl, et al. Weber, et al. Fergus, et al . Error rate Learning speed # training images Algorithm
31.
And another Comparison..
32.