32 Result(s)
within
English
Artificial Intelligence
Image Processing and Computer Vision
Dong-**ng Wang
Chapter
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Chapter and Conference Paper
Sequential Max-Margin Event Detectors
Many applications in computer vision (e.g., games, human computer interaction) require a reliable and early detector of visual events. Existing event detection methods rely on one-versus-all or multi-class cla...
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Chapter and Conference Paper
Hierarchical Convolutional Neural Network for Face Detection
In this paper, we propose a new approach of hierarchical convolutional neural network (CNN) for face detection. The first layer of our architecture is a binary classifier built on a deep convolutional neural n...
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Chapter and Conference Paper
One Simple Virtual Avatar System Based on Single Image
To establish virtual avatar systems at the computing environments with limited resources, we design such a system based on single image which can generate speech animation with different facial expressions. Fi...
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Chapter and Conference Paper
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
3D action recognition – analysis of human actions based on 3D skeleton data – becomes popular recently due to its succinctness, robustness, and view-invariant representation. Recent attempts on this problem su...
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Chapter and Conference Paper
A Siamese Long Short-Term Memory Architecture for Human Re-identification
Matching pedestrians across multiple camera views known as human re-identification (re-identification) is a challenging problem in visual surveillance. In the existing works concentrating on feature extraction...
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Chapter and Conference Paper
Unsupervised Visual Representation Learning by Graph-Based Consistent Constraints
Learning rich visual representations often require training on datasets of millions of manually annotated examples. This substantially limits the scalability of learning effective representations as labeled da...
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Chapter and Conference Paper
Towards Automatic Semantic Segmentation in Volumetric Ultrasound
3D ultrasound is rapidly emerging as a viable imaging modality for routine prenatal examinations. However, lacking of efficient tools to decompose the volumetric data greatly limits its widespread. In this pap...
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Chapter and Conference Paper
UAPD: Predicting Urban Anomalies from Spatial-Temporal Data
Urban city environments face the challenge of disturbances, which can create inconveniences for its citizens. These require timely detection and resolution, and more importantly timely preparedness on the part...
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Chapter and Conference Paper
Medical Image Synthesis with Context-Aware Generative Adversarial Networks
Computed tomography (CT) is critical for various clinical applications, e.g., radiation treatment planning and also PET attenuation correction in MRI/PET scanner. However, CT exposes radiation during acquisiti...
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Chapter and Conference Paper
Deformable Image Registration Based on Similarity-Steered CNN Regression
Existing deformable registration methods require exhaustively iterative optimization, along with careful parameter tuning, to estimate the deformation field between images. Although some learning-based method...
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Chapter and Conference Paper
Multi-context Deep Convolutional Features and Exemplar-SVMs for Scene Parsing
Scene parsing is a challenging task in computer vision field. The work of scene parsing is labeling every pixel in an image with its semantic category to which it belongs. In this paper, we solve this problem ...
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Chapter and Conference Paper
High Capacity Reversible Data Hiding with Contrast Enhancement
Reversible data hiding aims at recovering exactly the cover image from the marked image after extracting the hidden data. Reversible data hiding with contrast enhancement proposed by Wu et al. achieved a good eff...
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Chapter and Conference Paper
Quality Assessment of Palm Vein Image Using Natural Scene Statistics
Image quality has a great influence on the performance of non-contact biometric identification system. In order to acquire palm vein image with high-quality, an image quality assessment algorithm for palm vein...
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Chapter and Conference Paper
Image Forgery Detection Based on Semantic Image Understanding
Image forensics has been focusing on low-level visual features, paying little attention to high-level semantic information of the image. In this work, we propose the framework for image forgery detection based...
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Chapter and Conference Paper
Fine-Grained Segmentation Using Hierarchical Dilated Neural Networks
Image segmentation is a crucial step in many computer-aided medical image analysis tasks, e.g., automated radiation therapy. However, low tissue-contrast and large amounts of artifacts in medical images, i.e., CT...
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Chapter and Conference Paper
Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis
Autism spectrum disorder (ASD) is mainly diagnosed by the observation of core behavioral symptoms. Due to the absence of early biomarkers to detect infants either with or at-risk of ASD during the first postnatal...
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Chapter and Conference Paper
Learning to Navigate for Fine-Grained Classification
Fine-grained classification is challenging due to the difficulty of finding discriminative features. Finding those subtle traits that fully characterize the object is not straightforward. To handle this circum...
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Chapter and Conference Paper
Real-Time ‘Actor-Critic’ Tracking
In this work, we propose a novel tracking algorithm with real-time performance based on the ‘Actor-Critic’ framework. This framework consists of two major components: ‘Actor’ and ‘Critic’. The ‘Actor’ model ai...
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Chapter and Conference Paper
Quality Assessment of Fetal Head Ultrasound Images Based on Faster R-CNN
Clinically, the transthalamic plane of the fetal head is manually examined by sonographers to identify whether it is a standard plane. This examination routine is subjective, time-consuming and requires compre...
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Chapter and Conference Paper
Deep Gabor Scattering Network for Image Classification
Deep learning models obtain exponential ascension in the field of image classification in recent years, and have become the most active research branch in AI research. The success of deep learning prompts us t...
