Results 31 to 40 of about 263,469 (298)

Boosting Minority Class Prediction on Imbalanced Point Cloud Data

Applied Sciences, 2020
Data imbalance during the training of deep networks can cause the network to skip directly to learning minority classes. This paper presents a novel framework by which to train segmentation networks using imbalanced point cloud data.
Hsien-I Lin, Mihn Cong Nguyen
doaj   +1 more source

NeighborLoss: A Loss Function Considering Spatial Correlation for Semantic Segmentation of Remote Sensing Image

IEEE Access, 2021
House segmentation of remote sensing image based on deep learning has become the main segmentation method because it can automatically extract features.
Wei Yuan, Wenbo Xu
doaj   +1 more source

An imbalance-aware deep neural network for early prediction of preeclampsia.

PLoS ONE, 2022
Preeclampsia (PE) is a hypertensive complication affecting 8-10% of US pregnancies annually. While there is no cure for PE, aspirin may reduce complications for those at high risk for PE. Furthermore, PE disproportionately affects racial minorities, with
Rachel Bennett, Zuber D Mulla, Pavan Parikh, Alisse Hauspurg, Talayeh Razzaghi   +4 more
doaj   +1 more source

Cost-Sensitive Learning for Anomaly Detection in Imbalanced ECG Data Using Convolutional Neural Networks

Sensors, 2022
Arrhythmia detection algorithms based on deep learning are attracting considerable interest due to their vital role in the diagnosis of cardiac abnormalities.
Muhammad Zubair, Changwoo Yoon
doaj   +1 more source

Bayesian estimation of the Pareto model based on type-II censoring data by employing non-linear programming

Alexandria Engineering Journal
The main goal of this article is to determine the optimally weighted coefficients (Ω1and Ω2) of the balanced loss function of the form. LΚ,Ω,ξoΨ(σ),ξ=Ω1γσΚξo,ξ+Ω2γσΚΨ(σ),ξ;Ω1+Ω2=1.
Laila A. AL-Essa, Fuad S. Al-Duais, Walid Aydi, Afrah Y. AL-Rezami   +3 more
doaj   +1 more source

Improving Skin-Disease Classification Based on Customized Loss Function Combined With Balanced Mini-Batch Logic and Real-Time Image Augmentation

IEEE Access, 2020
Skin cancer is one of the most common cancers in the world. However, the disease is curable if detected in the beginning stage. Early detection of malignant lesions through accurate techniques and innovative technologies has a significant impact on ...
Tri-Cong Pham, Antoine Doucet, Chi-Mai Luong, Cong-Thanh Tran, Van-Dung Hoang   +4 more
doaj   +1 more source

ROC Curves, Loss Functions, and Distorted Probabilities in Binary Classification

Mathematics, 2022
The main purpose of this work is to study how loss functions in machine learning influence the “binary machines”, i.e., probabilistic AI models for predicting binary classification problems.
Phuong Bich Le, Zung Tien Nguyen
doaj   +1 more source

Improved Balanced Classification with Theoretically Grounded Loss Functions

CoRR
NeurIPS ...
Corinna Cortes, Mehryar Mohri, Yutao Zhong 0002   +2 more
openaire   +2 more sources

Time Toxicity in Wilms Tumor: Quantifying the Burden of Healthcare Interaction in the First Year After Diagnosis

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Wilms tumor (WT) treatment imposes a significant time burden on patients and their families. Time toxicity is a patient‐centered metric that quantifies the burden of healthcare interaction. We sought to define time toxicity in the first year after diagnosis of WT and hypothesized that it would increase as tumor stage and treatment ...
Caleb Q. Ashbrook, Veerain Gupta, Nicholas J. Clark, Vijay Rings, Lauren E. Corona, Douglass B. Clayton, Daniel J. Benedetti   +6 more
wiley   +1 more source

Class Balanced Loss for Image Classification

IEEE Access, 2020
In the study of image classification, neural network learning relies heavily on datasets. Due to variability in the difficulty of collecting images in reality, datasets tend to have class imbalance problems, which undoubtedly increases the difficulty of ...
Lin Wang, Chaoli Wang, Zhanquan Sun, Shuqun Cheng, Lei Guo   +4 more
doaj   +1 more source