A comprehensive survey of loss functions in machine learning
Q Wang, Y Ma, K Zhao, Y Tian - Annals of Data Science, 2020 - Springer
As one of the important research topics in machine learning, loss function plays an important
role in the construction of machine learning algorithms and the improvement of their …
role in the construction of machine learning algorithms and the improvement of their …
[HTML][HTML] Data-driven structural health monitoring and damage detection through deep learning: State-of-the-art review
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …
recent technological advancements in sensors, as well as high-speed internet and cloud …
Causal intervention for weakly-supervised semantic segmentation
We present a causal inference framework to improve Weakly-Supervised Semantic
Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by …
Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by …
[HTML][HTML] A spatial-temporal attention-based method and a new dataset for remote sensing image change detection
Remote sensing image change detection (CD) is done to identify desired significant
changes between bitemporal images. Given two co-registered images taken at different …
changes between bitemporal images. Given two co-registered images taken at different …
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the
world, having a severe impact on the health and life of many people globally. One of the …
world, having a severe impact on the health and life of many people globally. One of the …
[HTML][HTML] Clinically applicable AI system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography
Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel
coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid …
coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid …
Doubleu-net: A deep convolutional neural network for medical image segmentation
Semantic image segmentation is the process of labeling each pixel of an image with its
corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a …
corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a …
Semi-supervised semantic segmentation with cross-consistency training
In this paper, we present a novel cross-consistency based semi-supervised approach for
semantic segmentation. Consistency training has proven to be a powerful semi-supervised …
semantic segmentation. Consistency training has proven to be a powerful semi-supervised …
A survey of deep learning techniques for autonomous driving
The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
Learning enriched features for real image restoration and enhancement
With the goal of recovering high-quality image content from its degraded version, image
restoration enjoys numerous applications, such as in surveillance, computational …
restoration enjoys numerous applications, such as in surveillance, computational …