Nowadays Convolutional Neural Networks (CNNs) are being employed in a wide range of
industrial technologies for a variety of sectors, such as medical, automotive, aviation …

With the development of web technology, multi-modal or multi-view data has surged as a
major stream for big data, where each modal/view encodes individual property of data …

Multi-label image recognition has attracted considerable research attention and achieved
great success in recent years. Capturing label correlations is an effective manner to advance …

The task of multi-label image recognition is to predict a set of object labels that present in an
image. As objects normally co-occur in an image, it is desirable to model the label …

Reliable entity subtyping is paramount for therapy stratification in lung cancer.
Morphological evaluation remains the basis for entity subtyping and directs the application …

Multilabel image classification aims to assign images to multiple possible labels. In this task,
each image may be associated with multiple labels, making it more challenging than the …

In today's digital age, Convolutional Neural Networks (CNNs), a subset of Deep Learning
(DL), are widely used for various computer vision tasks such as image classification, object …

The key to leak detection and location in water supply pipelines is signal denoising and
feature extraction. First, in this paper, an improved spline-local mean decomposition …

In an ever-increasingly complex electromagnetic environment, multiple low probability of
intercept (LPI) radar emitters may transmit their own signals simultaneously on similar …

Quantification and reduction of uncertainty in deep-learning techniques have received much
attention but ignored how to characterize the imprecision caused by such uncertainty. In …