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Loss Functions in the Era of Semantic Segmentation: A Survey and Outlook

Loss Functions in the Era of Semantic Segmentation: A Survey and Outlook

8 December 2023
Reza Azad
Moein Heidary
Kadir Yilmaz
Michael Huttemann
Sanaz Karimijafarbigloo
Yuli Wu
Anke Schmeink
Dorit Merhof
    VLM
    SSeg
ArXivPDFHTML

Papers citing "Loss Functions in the Era of Semantic Segmentation: A Survey and Outlook"

17 / 17 papers shown
Title
MultiTaskVIF: Segmentation-oriented visible and infrared image fusion via multi-task learning
MultiTaskVIF: Segmentation-oriented visible and infrared image fusion via multi-task learning
Zixian Zhao
Andrew Howes
Xingchen Zhang
26
0
0
10 May 2025
Loss Functions in Deep Learning: A Comprehensive Review
Loss Functions in Deep Learning: A Comprehensive Review
Omar Elharrouss
Yasir Mahmood
Yassine Bechqito
Mohamed Adel Serhani
E. Badidi
Jamal Riffi
Hamid Tairi
38
0
0
05 Apr 2025
Dual-Task Learning for Dead Tree Detection and Segmentation with Hybrid Self-Attention U-Nets in Aerial Imagery
Dual-Task Learning for Dead Tree Detection and Segmentation with Hybrid Self-Attention U-Nets in Aerial Imagery
Anis Ur Rahman
Einari Heinaro
Mete Ahishali
Samuli Junttila
45
1
0
27 Mar 2025
Transport-Related Surface Detection with Machine Learning: Analyzing Temporal Trends in Madrid and Vienna
Transport-Related Surface Detection with Machine Learning: Analyzing Temporal Trends in Madrid and Vienna
Miguel Ureña Pliego
Rubén Martínez Marín
Nianfang Shi
Takeru Shibayama
Ulrich Leth
Miguel Marchamalo Sacristán
58
0
0
19 Mar 2025
Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene
Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene
Shengqiong Wu
Hao Fei
Jingkang Yang
X. Li
Juncheng Li
Hao Zhang
Tat-Seng Chua
53
0
0
19 Mar 2025
Steerable Pyramid Weighted Loss: Multi-Scale Adaptive Weighting for Semantic Segmentation
Renhao Lu
SSeg
94
0
0
09 Mar 2025
FloPE: Flower Pose Estimation for Precision Pollination
FloPE: Flower Pose Estimation for Precision Pollination
Rashik Shrestha
Madhav Rijal
T. Smith
Yu Gu
39
0
0
08 Mar 2025
GBT-SAM: Adapting a Foundational Deep Learning Model for Generalizable Brain Tumor Segmentation via Efficient Integration of Multi-Parametric MRI Data
GBT-SAM: Adapting a Foundational Deep Learning Model for Generalizable Brain Tumor Segmentation via Efficient Integration of Multi-Parametric MRI Data
Cecilia Diana-Albelda
Roberto Alcover-Couso
Álvaro García-Martín
Jesús Bescós
Marcos Escudero-Viñolo
50
1
0
06 Mar 2025
A margin-based replacement for cross-entropy loss
A margin-based replacement for cross-entropy loss
Michael W. Spratling
Heiko H. Schütt
68
0
0
21 Jan 2025
UU-Mamba: Uncertainty-aware U-Mamba for Cardiovascular Segmentation
UU-Mamba: Uncertainty-aware U-Mamba for Cardiovascular Segmentation
Ting Yu Tsai
Li Lin
Shu Hu
Connie W. Tsao
Xin Li
Ming-Ching Chang
Hongtu Zhu
Xin Wang
Mamba
48
1
0
22 Sep 2024
Deep Bayesian segmentation for colon polyps: Well-calibrated predictions
  in medical imaging
Deep Bayesian segmentation for colon polyps: Well-calibrated predictions in medical imaging
Daniela L. Ramos
Héctor J. Hortúa
UQCV
48
0
0
23 Jul 2024
Datacube segmentation via Deep Spectral Clustering
Datacube segmentation via Deep Spectral Clustering
A. Bombini
Fernando García-Avello Bofías
Caterina Bracci
Michele Ginolfi
Chiara Ruberto
90
1
0
31 Jan 2024
Foundational Models in Medical Imaging: A Comprehensive Survey and
  Future Vision
Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision
Bobby Azad
Reza Azad
Sania Eskandari
Afshin Bozorgpour
A. Kazerouni
I. Rekik
Dorit Merhof
VLM
MedIm
101
60
0
28 Oct 2023
Semi-supervised Multi-task Learning for Semantics and Depth
Semi-supervised Multi-task Learning for Semantics and Depth
Yufeng Wang
Yi-Hsuan Tsai
Wei-Chih Hung
Wenrui Ding
Shuo Liu
Ming-Hsuan Yang
31
18
0
14 Oct 2021
MISSFormer: An Effective Medical Image Segmentation Transformer
MISSFormer: An Effective Medical Image Segmentation Transformer
Xiaohong Huang
Zhifang Deng
Dandan Li
Xueguang Yuan
ViT
MedIm
95
174
0
15 Sep 2021
Unified Focal loss: Generalising Dice and cross entropy-based losses to
  handle class imbalanced medical image segmentation
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation
Michael Yeung
Evis Sala
Carola-Bibiane Schönlieb
L. Rundo
32
394
0
08 Feb 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
375
75,972
0
18 May 2015
1