32 Result(s)
within
English
Computer Science
Artificial Intelligence
Image Processing and Computer Vision
Dong-**ng Wang
Chapter
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Chapter and Conference Paper
The Sixth Visual Object Tracking VOT2018 Challenge Results
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers...
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Chapter and Conference Paper
Application of Growth Curve in Agricultural Scientific Research
This paper introduces the application of logistic curve in agricultural science, and gives a division method of parameter estimation of logistic curve. Because the logistic curve contains three parameters, it ...
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Chapter and Conference Paper
China’s Wine Import Industry: An Economic Analysis of Influencing Trade Factors
In recent years, China is undergoing a huge economic transformation since joining in World Trade Organization (WTO) and it has showed an increasing demand for wine. As China’s wine consumption market is increa...
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Chapter and Conference Paper
The Study of the Work Parameters of the Corn Harvester Cutter
In this paper, the analytical method of multivariate variance is applied to study the function of the various performance factors of the straight-edge cylindrical cutter. Research results indicate that the mai...
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Chapter and Conference Paper
Effects of Exogenous Gamma-Aminobutyric Acid on Absorption and Regulation of Ion in Wheat Under Salinity Stress
Gamma-aminobutyric acid (GABA), a four-carbon non-protein amino acid, is a significant component of the free amino acid pool, there are numerous reports that rapid and large increases in GABA levels occur in p...
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Chapter and Conference Paper
PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results
In this paper, we describe the Perceptual Image Restoration and Manipulation (PIRM) workshop challenge on spectral image super-resolution, motivate its structure and conclude on results obtained by the partici...
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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...
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Chapter and Conference Paper
Deep Attentional Features for Prostate Segmentation in Ultrasound
Automatic prostate segmentation in transrectal ultrasound (TRUS) is of essential importance for image-guided prostate biopsy and treatment planning. However, develo** such automatic solutions remains very ch...
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Chapter and Conference Paper
Generalizing Deep Models for Ultrasound Image Segmentation
Deep models are subject to performance drop when encountering appearance discrepancy, even on congeneric corpus in which objects share the similar structure but only differ slightly in appearance. This perform...
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Chapter and Conference Paper
Shot Boundary Detection with Spatial-Temporal Convolutional Neural Networks
Nowadays, digital videos have been widely leveraged to record and share various events and people’s daily life. It becomes urgent to provide automatic video semantic analysis and management for convenience. Sh...
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Chapter and Conference Paper
Structured Siamese Network for Real-Time Visual Tracking
Local structures of target objects are essential for robust tracking. However, existing methods based on deep neural networks mostly describe the target appearance from the global view, leading to high sensiti...
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Chapter and Conference Paper
PSDF Fusion: Probabilistic Signed Distance Function for On-the-fly 3D Data Fusion and Scene Reconstruction
We propose a novel 3D spatial representation for data fusion and scene reconstruction. Probabilistic Signed Distance Function (Probabilistic SDF, PSDF) is proposed to depict uncertainties in the 3D space. It is m...
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Chapter and Conference Paper
Learning 3D Keypoint Descriptors for Non-rigid Shape Matching
In this paper, we present a novel deep learning framework that derives discriminative local descriptors for 3D surface shapes. In contrast to previous convolutional neural networks (CNNs) that rely on renderin...
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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...
