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A Systematic Performance Analysis of Deep Perceptual Loss Networks:
  Breaking Transfer Learning Conventions

A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning Conventions

8 February 2023
G. Pihlgren
Konstantina Nikolaidou
Prakash Chandra Chhipa
Nosheen Abid
Rajkumar Saini
Fredrik Sandin
Marcus Liwicki
ArXivPDFHTML

Papers citing "A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning Conventions"

10 / 10 papers shown
Title
IMPACT: A Generic Semantic Loss for Multimodal Medical Image Registration
IMPACT: A Generic Semantic Loss for Multimodal Medical Image Registration
Valentin Boussot
Cédric Hémon
Jean-Claude Nunes
Jason Downling
Simon Rouzé
Caroline Lafond
Anaïs Barateau
Jean-Louis Dillenseger
51
0
0
31 Mar 2025
Seeing Eye to AI? Applying Deep-Feature-Based Similarity Metrics to Information Visualization
Sheng Long
Angelos Chatzimparmpas
Emma Alexander
Matthew Kay
Jessica Hullman
29
0
0
28 Feb 2025
A Framework for Evaluating Predictive Models Using Synthetic Image
  Covariates and Longitudinal Data
A Framework for Evaluating Predictive Models Using Synthetic Image Covariates and Longitudinal Data
Simon Deltadahl
Andreu Vall
Vijay Ivaturi
Niklas Korsbo
MedIm
16
0
0
21 Oct 2024
Khattat: Enhancing Readability and Concept Representation of Semantic
  Typography
Khattat: Enhancing Readability and Concept Representation of Semantic Typography
Ahmed Hussein
Alaa Elsetohy
Sama Hadhoud
Tameem Bakr
Yasser Rohaim
Badr AlKhamissi
VLM
34
0
0
01 Oct 2024
Rethinking HTG Evaluation: Bridging Generation and Recognition
Rethinking HTG Evaluation: Bridging Generation and Recognition
Konstantina Nikolaidou
George Retsinas
Giorgos Sfikas
Marcus Liwicki
29
1
0
04 Sep 2024
Can No-Reference Quality-Assessment Methods Serve as Perceptual Losses
  for Super-Resolution?
Can No-Reference Quality-Assessment Methods Serve as Perceptual Losses for Super-Resolution?
Egor Kashkarov
Egor Chistov
Ivan Molodetskikh
D. Vatolin
SupR
48
3
0
30 May 2024
Deep Perceptual Similarity is Adaptable to Ambiguous Contexts
Deep Perceptual Similarity is Adaptable to Ambiguous Contexts
G. Pihlgren
Fredrik Sandin
Marcus Liwicki
21
0
0
05 Apr 2023
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
297
10,216
0
16 Nov 2016
Neural Architecture Search with Reinforcement Learning
Neural Architecture Search with Reinforcement Learning
Barret Zoph
Quoc V. Le
264
5,326
0
05 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
PINN
3DV
252
36,362
0
25 Aug 2016
1