InverseForm: A Loss Function for Structured Boundary-Aware Segmentation [PDF]
Computer Vision and Pattern Recognition, 2021 We present a novel boundary-aware loss term for semantic segmentation using an inverse-transformation network, which efficiently learns the degree of parametric transformations between estimated and target boundaries.
Shubhankar Borse +3 more
semanticscholar +1 more source
Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning [PDF]
IEEE International Conference on Computer Vision, 2021 In few-shot learning scenarios, the challenge is to generalize and perform well on new unseen examples when only very few labeled examples are available for each task.
Sungyong Baik +5 more
semanticscholar +1 more source
clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation [PDF]
Computer Vision and Pattern Recognition, 2020 Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, the topology is their most important characteristic; particularly preserving connectedness: in the
Suprosanna Shit +8 more
semanticscholar +1 more source
The Real-World-Weight Cross-Entropy Loss Function: Modeling the Costs of Mislabeling [PDF]
IEEE Access, 2020 In this paper, we propose a new metric to measure goodness-of-fit for classifiers: the Real World Cost function. This metric factors in information about a real world problem, such as financial impact, that other measures like accuracy or F1 do not. This
Yaoshiang Ho, S. Wookey
semanticscholar +1 more source
Statistical Properties of the log-cosh Loss Function Used in Machine Learning [PDF]
arXiv.org, 2022 This paper analyzes a popular loss function used in machine learning called the log-cosh loss function. A number of papers have been published using this loss function but, to date, no statistical analysis has been presented in the literature.
Resve A. Saleh, A. Saleh
semanticscholar +1 more source
AutoLoss: Automated Loss Function Search in Recommendations [PDF]
Knowledge Discovery and Data Mining, 2021 Designing an effective loss function plays a crucial role in training deep recommender systems. Most existing works often leverage a predefined and fixed loss function that could lead to suboptimal recommendation quality and training efficiency.
Xiangyu Zhao +5 more
semanticscholar +1 more source
Fast and Accurate Road Crack Detection Based on Adaptive Cost-Sensitive Loss Function [PDF]
IEEE Transactions on Cybernetics, 2021 Numerous detection problems in computer vision, including road crack detection, suffer from exceedingly foreground–background imbalance. Fortunately, modification of loss function appears to solve this puzzle once and for all. In this article, we propose
Kai Li +3 more
semanticscholar +1 more source
AutoLossGen: Automatic Loss Function Generation for Recommender Systems [PDF]
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022 In recommendation systems, the choice of loss function is critical since a good loss may significantly improve the model performance. However, manually designing a good loss is a big challenge due to the complexity of the problem.
Zelong Li +3 more
semanticscholar +1 more source
A Novel Focal Tversky Loss Function With Improved Attention U-Net for Lesion Segmentation [PDF]
IEEE International Symposium on Biomedical Imaging, 2018 We propose a generalized focal loss function based on the Tversky index to address the issue of data imbalance in medical image segmentation. Compared to the commonly used Dice loss, our loss function achieves a better trade off between precision and ...
Nabila Abraham, N. Khan
semanticscholar +1 more source
Prediction of Interest Rate Using Artificial Neural Network and Novel Meta-Heuristic Algorithms [PDF]
Iranian Journal of Accounting, Auditing & Finance, 2021 One of the most parameters and variables in every economics is the interest rate. Government officials and lawmakers change interest rates for various purposes: controlling liquidity, inflation, and prices, Economic growth and development, lending, etc ...
Milad Shahvaroughi Farahani
doaj +1 more source