Change detection (CD) is a fundamental and important task for monitoring...
Remote sensing image change detection aims to identify the differences
b...
Buildings are the basic carrier of social production and human life; roa...
The efficacy of building footprint segmentation from remotely sensed ima...
Change detection (CD) is an important yet challenging task in the Earth
...
Weakly-supervised change detection (WSCD) aims to detect pixel-level cha...
Photoplethysmogram (PPG) signals are easily contaminated by motion artif...
Wearing face mask is an effective measure to reduce the risk of COVID-19...
High spectral resolution imagery of the Earth's surface enables users to...
Hyperspectral change detection plays an essential role of monitoring the...
In a federated learning (FL) system, malicious participants can easily e...
Very-high-resolution (VHR) remote sensing (RS) image change detection (C...
Multimodal headline utilizes both video frames and transcripts to genera...
Unsupervised multimodal change detection is a practical and challenging ...
Neural ranking models (NRMs) have achieved promising results in informat...
This paper designs a new and scientific environmental quality assessment...
Improving software performance is an important yet challenging part of t...
Recently, FCNs have attracted widespread attention in the CD field. In
p...
Recently, we have witnessed the bloom of neural ranking models in the
in...
Pre-trained transformers have recently clinched top spots in the gamut o...
The advance in machine learning (ML)-driven natural language process (NL...
Detecting and fixing bugs are two of the most important yet frustrating ...
We approach the important challenge of code autocompletion as an open-do...
As the COVID-19 epidemic began to worsen in the first months of 2020,
st...
Ranked list truncation is of critical importance in a variety of profess...
Malicious clients can attack federated learning systems by using malicio...
With the hyperspectral imaging technology, hyperspectral data provides
a...
Wuhan, the biggest city in China's central region with a population of m...
Change detection (CD) is one of the most vital applications in remote
se...
Classifying multi-temporal scene land-use categories and detecting their...
Variational autoencoders (VAEs) combine latent variables with amortized
...
Self-supervised pre-training has emerged as a powerful technique for nat...
Recently, deep learning has achieved promising performance in the change...
With the development of Earth observation technology, very-high-resoluti...
The ability of semantic reasoning over the sentence pair is essential fo...
Commonsense and background knowledge is required for a QA model to answe...
Recently, the pre-trained language model, BERT (Devlin et al.(2018)Devli...
This paper focuses on how to take advantage of external relational knowl...
Very high resolution (VHR) images provide abundant ground details and sp...
Unsupervised text style transfer aims to alter text styles while preserv...
Scene understanding of high resolution aerial images is of great importa...
Ranking models lie at the heart of research on information retrieval (IR...
The success of a fuzzing campaign is heavily depending on the quality of...
Change detection has been a hotspot in remote sensing technology for a l...
This paper describes a novel hierarchical attention network for reading
...
A fundamental trade-off between effectiveness and efficiency needs to be...
Optimizing data-intensive workflow execution is essential to many modern...
Object tracking is a hot topic in computer vision. Thanks to the booming...
Labeling each instance in a large dataset is extremely labor- and time-
...
Personalized search has been a hot research topic for many years and has...