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27 Result(s)
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Article
SPCNet: a strip pyramid ConvNeXt network for detection of road surface defects
Road surface defect detection plays an important role in the construction and maintenance of roads. However, the irregularity of road surface defects and the complexity of the background make the extraction of...
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Article
Data-driven approaches and model-based methods for detecting and locating leaks in water distribution systems: a literature review
Water distribution systems are made up of interconnected components that should allow water systems to meet demand, but leaks can waste enough water to limit supply. To limit financial losses, water utilities ...
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Chapter and Conference Paper
Detecting Escalation Level from Speech with Transfer Learning and Acoustic-Linguistic Information Fusion
Textual escalation detection has been widely applied to e-commerce companies’ customer service systems to pre-alert and prevent potential conflicts. Similarly, acoustic-based escalation detection systems are a...
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Chapter and Conference Paper
Patch-Level Instance-Group Discrimination with Pretext-Invariant Learning for Colitis Scoring
Inflammatory bowel disease (IBD), in particular ulcerative colitis (UC), is graded by endoscopists and this assessment is the basis for risk stratification and therapy monitoring. Presently, endoscopic charact...
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Chapter and Conference Paper
UNet-eVAE: Iterative Refinement Using VAE Embodied Learning for Endoscopic Image Segmentation
While endoscopy is routinely used for surveillance, high operator dependence demands robust automated image analysis methods. Automated segmentation of region-of-interest (ROI) that includes lesions, inflammat...
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Chapter and Conference Paper
ETH-TT: A Novel Approach for Detecting Ethereum Malicious Accounts
Ethereum, as the second generation of blockchain technology, it not only brings many advantages, but also spawns various malicious incidents. Ethereum’s anonymity makes it a hotbed of cybercrime, causing huge ...
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Chapter and Conference Paper
Improved Artifact Detection in Endoscopy Imaging Through Profile Pruning
Endoscopy is a highly operator dependent procedure. During any endoscopic surveillance of hollow organs, the presence of several imaging artifacts such as blur, specularity, floating debris and pixel saturatio...
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Chapter and Conference Paper
Fast Optimal Transport Artistic Style Transfer
Artistic style transfer plays an important role in the culture and entertainment industry. However, contemporary stylization approaches are suffering from two obstacles: 1) the low temporal efficiency and 2) t...
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Chapter and Conference Paper
AABC:ALBERT-BiLSTM-CRF Combining with Adapters
Pre-training models (PTMs) are language models pre-trained on a large corpus, which can learn general language representations through training tasks within the model. PTMs complete various NLP tasks by connec...
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Chapter and Conference Paper
TS-Bert: Time Series Anomaly Detection via Pre-training Model Bert
Anomaly detection of time series is of great importance in data mining research. Current state of the art suffer from scalability, over reliance on labels and high false positives. To this end, a novel framewo...
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Chapter and Conference Paper
RPT: Learning Point Set Representation for Siamese Visual Tracking
While remarkable progress has been made in robust visual tracking, accurate target state estimation still remains a highly challenging problem. In this paper, we argue that this issue is closely related to the...
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Chapter and Conference Paper
CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing
In contrast to great success of memory-consuming face editing methods at a low resolution, to manipulate high-resolution (HR) facial images, i.e., typically larger than
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Chapter and Conference Paper
The Eighth Visual Object Tracking VOT2020 Challenge Results
The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers publish...
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Book
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Chapter
Introduction
In this chapter, we first give the background for writing this monograph. Then, we provide a formal definition of multiview machine learning and discuss its difference and similarities with related concepts da...
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Chapter and Conference Paper
A Conditional Random Fields Based Framework for Multiview Sequential Data Modeling
Multiview learning has gained much attention due to the increasing amount of multiview data which are collected from different sources or can be characterized by different types of features. How to properly ha...
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Chapter and Conference Paper
Design of Morphing Wing Leading Edge with Compliant Mechanism
This paper describes a design process of morphing wing leading edge with a compliant mechanism. A bending-shape design method by thickness optimization of variable cross-section beam is proposed to solve the m...
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Chapter
View Construction
In most real applications, data are represented by a single view, which is difficult to apply in multiview learning. In this Chapter, we introduce six view construction methods to generate new views from the o...
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Chapter
Multiview Semi-supervised Learning
Semi-supervised learning is concerned with such learning scenarios where only a small portion of training data are labeled. In multiview settings, unlabeled data can be used to regularize the prediction functi...
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Chapter
Multiview Supervised Learning
Multiview supervised learning algorithm can exploit the multiview nature of the data by the consensus of the views, that is, to seek predictors from different views that agree on the same example. In this chap...
