Defect identification of wind turbine blades based on defect semantic features with transfer feature extractor
The monitoring of the status of the wind turbine blades is significant for the wind generation system and currently mainly dependent on manual visual inspections. The variance of the blade defects and the lack of the blade defect ...
ν-projection twin support vector machine for pattern classification
- A nonparallel projection classifier (ν-PTSVM) with theoretically sound parameter ν is proposed.
In this paper, we improve the projection twin support vector machine (PTSVM) to a novel nonparallel classifier, termed as ν-PTSVM. Specifically, our ν-PTSVM aims to seek an optimal projection for each class such that, in each ...
A novel approach inspired by optic nerve characteristics for few-shot occluded face recognition
Although there has been a growing body of work for face recognition, it is still a challenging task for faces under occlusion with limited training samples. In this work, we propose a novel framework to address the problem of few-shot ...
An efficient model-level fusion approach for continuous affect recognition from audiovisual signals
Continuous affect recognition has a huge potential in human computer interaction applications. How to efficiently fuse speech and facial information for inferring the affective state of a person from data captured in real-world ...
A novel geodesic flow kernel based domain adaptation approach for intelligent fault diagnosis under varying working condition
Domain adaptation techniques have drawn much attention for mechanical defect diagnosis in recent years. Nevertheless, the traditional domain adaptation approaches may suffer two shortcomings: (1) Poor performance is obtained for many ...
Position-aware context attention for session-based recommendation
In session-based recommendation scenarios where user profiles are not available, predicting their behaviors is a challenging problem. Previous dominant methods to solve this problem are RNN-based models. Recently, attention mechanisms ...
Global µ-stability of neutral-type impulsive complex-valued BAM neural networks with leakage delay and unbounded time-varying delays
This paper investigates the existence and uniqueness of the equilibrium point and its global µ-stability for neutral-type impulsive complex-valued bidirectional associative memory neural networks with leakage delay and unbounded time-...
Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression
To solve the problem of the inaccurate prediction on remaining useful life (RUL) for lithium-ion battery, we proposed an integrated algorithm which combines adaptive unscented kalman filter (AUKF) and genetic algorithm optimized ...
Extreme semi-supervised learning for multiclass classification
Semi-Supervised Support Vector Machines (S3VMs) provide a powerful framework for Semi-Supervised Learning (SSL) tasks which leverage widely available unlabeled data to improve performance. However, there exist three ...
RBPNET: An asymptotic Residual Back-Projection Network for super-resolution of very low-resolution face image
The super-resolution of a very low-resolution face image is a challenge task in single image super-resolution. Most of deep learning methods learn a non-linear mapping of input-to-target space by one-step upsampling. These methods are ...
Prior information constrained alternating direction method of multipliers for longitudinal compressive sensing MR imaging
- Ruirui Kang,
- Danni Ai,
- Gangrong Qu,
- Qingbo Li,
- Xu Li,
- Yurong Jiang,
- Yong Huang,
- Hong Song,
- Yongtian Wang,
- Jian Yang
Sparsity is widely utilized for magnetic resonance imaging (MRI) to reduce k-space sampling. In many clinical MRI scenarios, existing similarity within a series of MRI images and between different contrasts in the same scan can be used ...
A 1-norm regularized linear programming nonparallel hyperplane support vector machine for binary classification problems
This research proposes a 1-norm regularized linear programming nonparallel hyperplane support vector machine (LNSVM) model to solve binary classification problems and enhance the robustness performance. Numerous nonparallel support ...
Triple-adjacent-frame generative network for blind video motion deblurring
- In the coarse-to-fine process, we conceive a bidirectional temporal feature transfer that passes the internal features of a blurry video frame on to the ...
Photos and videos captured by handheld imaging devices are often accompanied by unwanted blur because of hand jitters and fast movement of objects during the exposure time. Most previous studies discussed single image deblurring and ...
Integrating deep convolutional neural networks with marker-controlled watershed for overlapping nuclei segmentation in histopathology images
Nuclei segmentation in histopathology images plays a crucial role in the morphological quantitative analysis of tissue structure and has become a hot research topic. Though numerous efforts have been tried in this research area, the ...
Robust deep auto-encoding Gaussian process regression for unsupervised anomaly detection
Unsupervised anomaly detection (AD) is of great importance in both fundamental machine learning researches and industrial applications. Previous approaches have achieved great advance in improving the performance of unsupervised AD ...
Further results on mean-square exponential input-to-state stability of time-varying delayed BAM neural networks with Markovian switching
This paper mainly discusses the input-to-state stability for BAM neural networks with time-varying delays and Markov jump parameters. Considering the system with Markov jump parameters, we select the improved criterion, namely mean-...
EPAN: Effective parts attention network for scene text recognition
- We propose the new EPAN framework for the flexible and robust recognition of scene text.
For most previous attention-based scene text recognition methods, images are transformed into high-level feature vectors that form a feature map with height equal to one. Such vectors may contain unnecessary noise that limits ...
Text classification using capsules
This paper presents an empirical exploration of the use of capsule networks for text classification. While it has been shown that capsule networks are effective for image classification, the research regarding their validity in the ...
Multi-block statistics local kernel principal component analysis algorithm and its application in nonlinear process fault detection
It is vital for fault detection technology to extract features of industrial process data effectively. Local kernel principal component analysis (LKPCA) has proved its good performance in preserving global and local structural ...
Coarse-to-fine salient object detection with low-rank matrix recovery
Low-rank matrix recovery (LRMR) has recently been applied to saliency detection by decomposing image features into a low-rank component associated with background and a sparse component associated with visual salient regions. Despite ...
Visual abstraction and exploration of large-scale geographical social media data
- A rapid sampling model is employed to retain the topic distribution of social media datasets.
Display Omitted
AbstractA great deal of text and geographical information is provided in the geo-tagged social media data, which offers unprecedented opportunities to get insights into the social behaviors across different local areas. With the increasing ...