133 Result(s)
within
English
Image Processing and Computer Vision
Machine Learning
**ze Shen
Chapter
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Chapter and Conference Paper
Intrusion Detection Using Temporal Convolutional Networks
Intrusion detection system is an important network security facility. With the fast development of information technology, the information security is getting more serious. On the other side, making the IT equ...
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Chapter and Conference Paper
Learnable Gabor Convolutional Networks
Commonly used convolutional operation does not have the ability to learn invariant information of images. However, some handcrafted image feature extractors, like Gabor wavelets, are robust to object’s scale ...
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Chapter and Conference Paper
Robust Segmentation of Nucleus in Histopathology Images via Mask R-CNN
Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed ...
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Chapter and Conference Paper
Automatic Brain Tumor Segmentation with Domain Adaptation
Deep convolution neural networks, in particular, the encoder-decoder networks, have been extensively used in image segmentation. We develop a deep learning approach for tumor segmentation by combining a modifi...
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Chapter and Conference Paper
An Expert Validation Framework for Improving the Quality of Crowdsourced Clustering
Crowdclustering is a cost-effective mechanism that learns a cluster structure from data and crowdsourced human pairwise labels. Though some initial efforts have shown some effectiveness of crowdclustering, per...
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Chapter and Conference Paper
Correction to: Single Image Super-Resolution via a Holistic Attention Network
In the originally published version of chapter 12, the first affiliation stated a wrong city and country. This has been corrected.
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Chapter and Conference Paper
DDU-Nets: Distributed Dense Model for 3D MRI Brain Tumor Segmentation
Segmentation of brain tumors and their subregions remains a challenging task due to their weak features and deformable shapes. In this paper, three patterns (cross-skip, skip-1 and skip-2) of distributed dense...
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Chapter and Conference Paper
Underwater Enhancement Model via Reverse Dark Channel Prior
The interference of suspended particles causes the problems of color distortion, haze effect and visibility reduction in complex underwater environment. However, existing methods for enhancement often result i...
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Chapter and Conference Paper
Domain Adaptation for Eye Segmentation
Domain adaptation (DA) has been widely investigated as a framework to alleviate the laborious task of data annotation for image segmentation. Most DA investigations operate under the unsupervised domain adapt...
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Chapter and Conference Paper
Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-site Neuroimaging Data
Deep learning has demonstrated its superiority in automated identification of brain dementia based on neuroimaging data, such as structural MRIs. Previous methods typically assume that multi-site data are samp...
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Chapter and Conference Paper
Reconstruction and Re-ranking: A Simple and Effective Approach for Question Answering
With the rapid growth of knowledge bases (KBs), question answering over knowledge base, a.k.a. KBQA has drawn huge attention in recent years. Most of the existing methods follow the simply matching method and ...
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Chapter and Conference Paper
Assessment and Application Research on the Carrying Capacity of Township Power Supply Station Based on Big Data Analysis
At present, the grid division of township power supply stations lacks guiding opinions, the grid division principle of each unit is not unified, and the assessment of the carrying capacity of each station has ...
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Chapter and Conference Paper
A New Method Combining DNA Shape Features to Improve the Prediction Accuracy of Transcription Factor Binding Sites
Identifying transcription factor (TF) binding sites (TFBSs) has play an important role in the computational inference of gene regulation. With the development of high-throughput technologies, there have been m...
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Chapter and Conference Paper
Two-Stage Learning Brain Storm Optimizer
Brain storm optimizer (BSO), a new swarm intelligence paradigm inspired from the human brainstorming process, have received a surge of attentions. However, the original BSO easily suffers from the premature co...
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Chapter and Conference Paper
Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning
The performance of deep learning based methods strongly relies on the number of datasets used for training. Many efforts have been made to increase the data in the medical image analysis field. However, unlike...
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Chapter and Conference Paper
Detection of High-Risk Depression Groups Based on Eye-Tracking Data
Depression is the most common psychiatric disorder in the general population. An effective treatment of depression requires early detection. In reschedule this paper, a novel algorithm is presented based on ey...
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Chapter and Conference Paper
A Robust Automatic Method for Removing Projective Distortion of Photovoltaic Modules from Close Shot Images
Partial shading and hot spots may cause power loss and sometimes irreversible damage of photovoltaic (PV) modules. In order to evaluate the power generation of PV modules, it is necessary to calculate the area...
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Chapter and Conference Paper
Hybrid Labels for Brain Tumor Segmentation
The accurate automatic segmentation of brain tumors enhances the probability of survival rate. Convolutional Neural Network (CNN) is a popular automatic approach for image evaluations. CNN provides excellent r...
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Chapter and Conference Paper
cuRadiomics: A GPU-Based Radiomics Feature Extraction Toolkit
Radiomics is widely-used in imaging based clinical studies as a way of extracting high-throughput image descriptors. However, current tools for extracting radiomics features are generally run on CPU only, whic...
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Chapter and Conference Paper
Multi-model Network for Fine-Grained Cross-Media Retrieval
With the development of Internet, the forms of web data are rapidly increasing. However, existing cross-media retrieval methods mainly focus on coarse-grained, which is far from being satisfied in practical ap...
