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Is it enough to optimize CNN architectures on ImageNet?
v1v2v3v4 (latest)

Is it enough to optimize CNN architectures on ImageNet?

16 March 2021
Lukas Tuggener
Jürgen Schmidhuber
Thilo Stadelmann
ArXiv (abs)PDFHTML

Papers citing "Is it enough to optimize CNN architectures on ImageNet?"

10 / 10 papers shown
Beyond ImageNet: Understanding Cross-Dataset Robustness of Lightweight Vision Models
Beyond ImageNet: Understanding Cross-Dataset Robustness of Lightweight Vision Models
Weidong Zhang
Pak Lun Kevin Ding
Huan Liu
169
1
0
01 Nov 2025
Deep Neural Networks for Automatic Speaker Recognition Do Not Learn
  Supra-Segmental Temporal Features
Deep Neural Networks for Automatic Speaker Recognition Do Not Learn Supra-Segmental Temporal FeaturesPattern Recognition Letters (PR), 2023
Daniel Neururer
Volker Dellwo
Thilo Stadelmann
367
4
0
01 Nov 2023
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection
  in Industrial Time Series: Methods, Applications, and Directions
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and DirectionsIEEE Access (IEEE Access), 2023
Peng Yan
Ahmed Abdulkadir
Paul-Philipp Luley
Matthias Rosenthal
Gerrit A. Schatte
Benjamin Grewe
Thilo Stadelmann
AI4TS
365
150
0
11 Jul 2023
Does progress on ImageNet transfer to real-world datasets?
Does progress on ImageNet transfer to real-world datasets?Neural Information Processing Systems (NeurIPS), 2023
Alex Fang
Simon Kornblith
Ludwig Schmidt
VLM
241
53
0
11 Jan 2023
Image Classification with Small Datasets: Overview and Benchmark
Image Classification with Small Datasets: Overview and BenchmarkIEEE Access (IEEE Access), 2022
Lorenzo Brigato
Björn Barz
Luca Iocchi
Joachim Denzler
VLM
274
30
0
23 Dec 2022
Analysis of Deep Learning Architectures and Efficacy of Detecting Forest
  Fires
Analysis of Deep Learning Architectures and Efficacy of Detecting Forest Fires
Ryan Marinelli
249
0
0
08 Dec 2022
One Network Doesn't Rule Them All: Moving Beyond Handcrafted
  Architectures in Self-Supervised Learning
One Network Doesn't Rule Them All: Moving Beyond Handcrafted Architectures in Self-Supervised Learning
Sharath Girish
Debadeepta Dey
Neel Joshi
Vibhav Vineet
S. Shah
C. C. T. Mendes
Abhinav Shrivastava
Yale Song
SSL
267
2
0
15 Mar 2022
Tune It or Don't Use It: Benchmarking Data-Efficient Image
  Classification
Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification
Lorenzo Brigato
Björn Barz
Luca Iocchi
Joachim Denzler
216
20
0
30 Aug 2021
FEAR: A Simple Lightweight Method to Rank Architectures
FEAR: A Simple Lightweight Method to Rank Architectures
Debadeepta Dey
Shital C. Shah
Sébastien Bubeck
OOD
252
4
0
07 Jun 2021
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable ConvolutionsComputer Vision and Pattern Recognition (CVPR), 2016
François Chollet
MDEBDLPINN
3.6K
17,433
0
07 Oct 2016
1
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