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Learning Transferable Architectures for Scalable Image Recognition

Learning Transferable Architectures for Scalable Image Recognition

21 July 2017
Barret Zoph
Vijay Vasudevan
Jonathon Shlens
Quoc V. Le
ArXivPDFHTML

Papers citing "Learning Transferable Architectures for Scalable Image Recognition"

50 / 874 papers shown
Title
Regularizing Meta-Learning via Gradient Dropout
Regularizing Meta-Learning via Gradient Dropout
Hung-Yu Tseng
Yi-Wen Chen
Yi-Hsuan Tsai
Sifei Liu
Yen-Yu Lin
Ming-Hsuan Yang
16
34
0
13 Apr 2020
Meta-Learning in Neural Networks: A Survey
Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
OOD
93
1,935
0
11 Apr 2020
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A
  Review
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review
Yaodong Cui
Ren‐Hao Chen
Wenbo Chu
Long Chen
Daxin Tian
Ying Li
Dongpu Cao
3DPC
32
385
0
10 Apr 2020
Improved Residual Networks for Image and Video Recognition
Improved Residual Networks for Image and Video Recognition
Ionut Cosmin Duta
Li Liu
Fan Zhu
Ling Shao
SSeg
AI4TS
10
170
0
10 Apr 2020
A Neural Architecture Search based Framework for Liquid State Machine
  Design
A Neural Architecture Search based Framework for Liquid State Machine Design
Shuo Tian
Lianhua Qu
Kai Hu
Nan Li
Lei Wang
Weixia Xu
33
28
0
07 Apr 2020
Evolving Normalization-Activation Layers
Evolving Normalization-Activation Layers
Hanxiao Liu
Andrew Brock
Karen Simonyan
Quoc V. Le
19
79
0
06 Apr 2020
Adaptive Partial Scanning Transmission Electron Microscopy with
  Reinforcement Learning
Adaptive Partial Scanning Transmission Electron Microscopy with Reinforcement Learning
Jeffrey M. Ede
24
12
0
06 Apr 2020
Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio
Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio
Zhengsu Chen
J. Niu
Lingxi Xie
Xuefeng Liu
Longhui Wei
Qi Tian
27
12
0
06 Apr 2020
Deep learning approaches in food recognition
Deep learning approaches in food recognition
C. Kiourt
George Pavlidis
Stella Markantonatou
13
27
0
04 Apr 2020
A Generic Graph-based Neural Architecture Encoding Scheme for
  Predictor-based NAS
A Generic Graph-based Neural Architecture Encoding Scheme for Predictor-based NAS
Xuefei Ning
Yin Zheng
Tianchen Zhao
Yu Wang
Huazhong Yang
AI4CE
32
99
0
04 Apr 2020
Neural Architecture Generator Optimization
Neural Architecture Generator Optimization
Binxin Ru
P. Esperança
Fabio Maria Carlucci
20
40
0
03 Apr 2020
Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint
  Decision and Feature Aggregation
Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation
Peng Sun
Jiaxiang Wu
Songyuan Li
Peiwen Lin
Junzhou Huang
Xi Li
SSeg
19
13
0
31 Mar 2020
MTL-NAS: Task-Agnostic Neural Architecture Search towards
  General-Purpose Multi-Task Learning
MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
Yuan Gao
Haoping Bai
Zequn Jie
Jiayi Ma
Kui Jia
Wei Liu
29
94
0
31 Mar 2020
MUXConv: Information Multiplexing in Convolutional Neural Networks
MUXConv: Information Multiplexing in Convolutional Neural Networks
Zhichao Lu
Kalyanmoy Deb
Vishnu Boddeti
22
44
0
31 Mar 2020
Disturbance-immune Weight Sharing for Neural Architecture Search
Disturbance-immune Weight Sharing for Neural Architecture Search
Shuaicheng Niu
Jiaxiang Wu
Yifan Zhang
Yong Guo
P. Zhao
Junzhou Huang
Mingkui Tan
15
27
0
29 Mar 2020
DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search
DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search
Xiyang Dai
Dongdong Chen
Mengchen Liu
Yinpeng Chen
Lu Yuan
24
20
0
27 Mar 2020
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level
  Reformulation
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation
Chaoyang He
Haishan Ye
Li Shen
Tong Zhang
32
128
0
27 Mar 2020
DCNAS: Densely Connected Neural Architecture Search for Semantic Image
  Segmentation
DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation
Xiong Zhang
Hongmin Xu
Hong Mo
Jianchao Tan
Cheng Yang
Lei Wang
Wenqi Ren
AI4CE
29
91
0
26 Mar 2020
Hit-Detector: Hierarchical Trinity Architecture Search for Object
  Detection
Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
Jianyuan Guo
Kai Han
Yunhe Wang
Chao Zhang
Zhaohui Yang
Hanxue Wu
Xinghao Chen
Chang Xu
22
99
0
26 Mar 2020
Circumventing Outliers of AutoAugment with Knowledge Distillation
Circumventing Outliers of AutoAugment with Knowledge Distillation
Longhui Wei
Anxiang Xiao
Lingxi Xie
Xin Chen
Xiaopeng Zhang
Qi Tian
24
62
0
25 Mar 2020
A Systematic Evaluation: Fine-Grained CNN vs. Traditional CNN
  Classifiers
A Systematic Evaluation: Fine-Grained CNN vs. Traditional CNN Classifiers
Saeed Anwar
Nick Barnes
L. Petersson
19
6
0
24 Mar 2020
A Survey of Methods for Low-Power Deep Learning and Computer Vision
A Survey of Methods for Low-Power Deep Learning and Computer Vision
Abhinav Goel
Caleb Tung
Yung-Hsiang Lu
George K. Thiruvathukal
VLM
15
92
0
24 Mar 2020
Meta Pseudo Labels
Meta Pseudo Labels
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
262
658
0
23 Mar 2020
Learning Dynamic Routing for Semantic Segmentation
Learning Dynamic Routing for Semantic Segmentation
Yanwei Li
Lin Song
Yukang Chen
Zeming Li
Xinming Zhang
Xingang Wang
Jian Sun
SSeg
88
163
0
23 Mar 2020
BS-NAS: Broadening-and-Shrinking One-Shot NAS with Searchable Numbers of
  Channels
BS-NAS: Broadening-and-Shrinking One-Shot NAS with Searchable Numbers of Channels
Zan Shen
Jiang Qian
Bojin Zhuang
Shaojun Wang
Jing Xiao
28
5
0
22 Mar 2020
Review of data analysis in vision inspection of power lines with an
  in-depth discussion of deep learning technology
Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology
Xinyu Liu
Xiren Miao
Hao Jiang
Jia Chen
25
11
0
22 Mar 2020
A novel Deep Structure U-Net for Sea-Land Segmentation in Remote Sensing
  Images
A novel Deep Structure U-Net for Sea-Land Segmentation in Remote Sensing Images
Pourya Shamsolmoali
Masoumeh Zareapoor
Ruili Wang
Huiyu Zhou
Jie Yang
SSeg
14
99
0
17 Mar 2020
Efficient Bitwidth Search for Practical Mixed Precision Neural Network
Efficient Bitwidth Search for Practical Mixed Precision Neural Network
Yuhang Li
Wei Wang
Haoli Bai
Ruihao Gong
Xin Dong
F. Yu
MQ
21
20
0
17 Mar 2020
Tidying Deep Saliency Prediction Architectures
Tidying Deep Saliency Prediction Architectures
N. Reddy
Samyak Jain
P. Yarlagadda
Vineet Gandhi
22
48
0
10 Mar 2020
How to Train Your Super-Net: An Analysis of Training Heuristics in
  Weight-Sharing NAS
How to Train Your Super-Net: An Analysis of Training Heuristics in Weight-Sharing NAS
Kaicheng Yu
René Ranftl
Mathieu Salzmann
27
34
0
09 Mar 2020
Searching Central Difference Convolutional Networks for Face
  Anti-Spoofing
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
Zitong Yu
Chenxu Zhao
Zezheng Wang
Yunxiao Qin
Z. Su
Xiaobai Li
Feng Zhou
Guoying Zhao
CVBM
67
411
0
09 Mar 2020
Machine Learning based Anomaly Detection for 5G Networks
Machine Learning based Anomaly Detection for 5G Networks
Jordan Lam
R. Abbas
43
73
0
07 Mar 2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real
Chen Liang
David R. So
Quoc V. Le
39
220
0
06 Mar 2020
Accelerator-aware Neural Network Design using AutoML
Accelerator-aware Neural Network Design using AutoML
Suyog Gupta
Berkin Akin
25
66
0
05 Mar 2020
Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision
  Applications
Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications
Chinthaka Gamanayake
Lahiru Jayasinghe
Benny Kai Kiat Ng
Chau Yuen
VLM
23
45
0
05 Mar 2020
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural
  Networks for Edge Devices
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices
Byung Hoon Ahn
Jinwon Lee
J. Lin
Hsin-Pai Cheng
Jilei Hou
H. Esmaeilzadeh
76
55
0
04 Mar 2020
BATS: Binary ArchitecTure Search
BATS: Binary ArchitecTure Search
Adrian Bulat
Brais Martínez
Georgios Tzimiropoulos
MQ
25
67
0
03 Mar 2020
NAS-Count: Counting-by-Density with Neural Architecture Search
NAS-Count: Counting-by-Density with Neural Architecture Search
Yutao Hu
Xiaolong Jiang
Xuhui Liu
Baochang Zhang
Jungong Han
Xianbin Cao
David Doermann
38
89
0
29 Feb 2020
Semi-Supervised Neural Architecture Search
Semi-Supervised Neural Architecture Search
Renqian Luo
Xu Tan
Rui Wang
Tao Qin
Enhong Chen
Tie-Yan Liu
13
88
0
24 Feb 2020
SNIFF: Reverse Engineering of Neural Networks with Fault Attacks
SNIFF: Reverse Engineering of Neural Networks with Fault Attacks
J. Breier
Dirmanto Jap
Xiaolu Hou
S. Bhasin
Yang Liu
17
53
0
23 Feb 2020
A$^3$: Accelerating Attention Mechanisms in Neural Networks with
  Approximation
A3^33: Accelerating Attention Mechanisms in Neural Networks with Approximation
Tae Jun Ham
Sungjun Jung
Seonghak Kim
Young H. Oh
Yeonhong Park
...
Jung-Hun Park
Sanghee Lee
Kyoung Park
Jae W. Lee
D. Jeong
24
213
0
22 Feb 2020
DSNAS: Direct Neural Architecture Search without Parameter Retraining
DSNAS: Direct Neural Architecture Search without Parameter Retraining
Shou-Yong Hu
Sirui Xie
Hehui Zheng
Chunxiao Liu
Jianping Shi
Xunying Liu
Dahua Lin
24
130
0
21 Feb 2020
Learning Architectures for Binary Networks
Learning Architectures for Binary Networks
Dahyun Kim
Kunal Pratap Singh
Jonghyun Choi
MQ
25
44
0
17 Feb 2020
How to 0wn NAS in Your Spare Time
How to 0wn NAS in Your Spare Time
Sanghyun Hong
Michael Davinroy
Yigitcan Kaya
Dana Dachman-Soled
Tudor Dumitras
33
36
0
17 Feb 2020
CBIR using features derived by Deep Learning
CBIR using features derived by Deep Learning
S. Maji
Smarajit Bose
VLM
3DV
23
40
0
13 Feb 2020
Classifying the classifier: dissecting the weight space of neural
  networks
Classifying the classifier: dissecting the weight space of neural networks
Gabriel Eilertsen
Daniel Jonsson
Timo Ropinski
Jonas Unger
Anders Ynnerman
6
53
0
13 Feb 2020
Machine Learning in Python: Main developments and technology trends in
  data science, machine learning, and artificial intelligence
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence
S. Raschka
Joshua Patterson
Corey J. Nolet
AI4CE
29
484
0
12 Feb 2020
To Share or Not To Share: A Comprehensive Appraisal of Weight-Sharing
To Share or Not To Share: A Comprehensive Appraisal of Weight-Sharing
Aloïs Pourchot
Alexis Ducarouge
Olivier Sigaud
11
20
0
11 Feb 2020
Impact of ImageNet Model Selection on Domain Adaptation
Impact of ImageNet Model Selection on Domain Adaptation
Youshan Zhang
Brian D. Davison
FAtt
OOD
VLM
39
34
0
06 Feb 2020
Learning Test-time Augmentation for Content-based Image Retrieval
Learning Test-time Augmentation for Content-based Image Retrieval
Osman Tursun
Simon Denman
Sridha Sridharan
Clinton Fookes
21
6
0
05 Feb 2020
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