检索结果-内蒙古大学图书馆

4th International Conference on Mathematics and Artificial Intelligence, ICMAI 2019

作者： Mubashir, Muhammad Ahmed, Md Rishad Ahmad, Maqsood Siddiqui, Sarah Ali Ahmad, Mudaser Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China Khwaja Fareed University of Engineering and Information Technology Pakistan Macquarie University Sydney Australia. The Islamia University of Bahawalpur Pakistan

ISBN: (纸本)9781450362580

Pulse diagnosis has been a requisite facet in traditional Chinese medicine as well as in western medicine, yet the prognosis of lung cancer hinged on wrist pulse analysis entails the quotidian approaches. In spite of diagnosing the lung cancer, in traditional methods, the identification stratagem is divaricated into assorted steps: analysis of signals procured, synthetic extraction and selection of features, and subsequently the classification. However, the vague and mundane feature selection and signal analysis steers to the inadequate classification accuracy due to intrinsic deficiencies. In this study, we have proposed a novel deep convolutional neural network (DCNN) based approach to discern the lung cancer against the acquired wrist pulse signals. In order to ensnare the features, vanquishing the overfitting, a 1- dimensional 15-layers DCNN model is devised hinged on 1-D convolutional, batch normalization, and pooling layers. Considering the instinctive feature extraction, from the experimental data comprised of 45,969 samples of 16 lung cancer and 20 healthy individuals, assorted units are heaped in the lodged DCNN. The experimental comparison with the stateof- art deep neural networks (DNNs) and conventional methods evinced that our lodged approach conquer the deficiencies of conventional signal processing and manual feature selection approaches. Finally, the results, with the validation precision of 97.67%, outperform the recent existing approach for lung cancer recognition. © 2019 Association for computing Machinery.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Automatic Segmentation of Nasopharyngeal Carcinoma in CT Images Using Dual Attention and Edge Detection 48

Automatic Segmentation of Nasopharyngeal Carcinoma in CT Ima...

引用

48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Wang, Qizhi Huang, Wei Zhang, Yuan Li, Xuanya Ye, Xiongjun Hu, Kai Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan411105 China The First Hospital of Changsha Department of Radiology Changsha410005 China Baidu Inc. Beijing100085 China Chinese Academy of Medical Sciences Peking Union Medical College National Cancer Center Cancer Hospital Beijing100021 China

ISBN: (纸本)9781728163277

Nasopharyngeal carcinoma (NPC) is a malignant tumor with a high incidence. Accurate segmentation of the tumor region in Computed Tomography (CT) images of NPC is the key to treatment. However, the features of uneven grayscale values and hazy boundaries of NPC regions make accurate NPC segmentation particularly challenging. To address these problems, we propose an accurate and effective NPC segmentation method using Dual Attention and Edge Detection Convolutional Neural Network (DAED-Net). Firstly, we combine a 2.5D convolutional neural network with UNet++ and propose a new backbone called Dual-dimension Dense UNet (DD-UNet), which can extract more beneficial features from 3D images. Secondly, a Dual Attention Module (DAM) is proposed to help the model better segment the target region of NPC by efficiently collecting spatial and channel attention information from feature maps. Moreover, an Edge Detection Module (EDM) is introduced in the network to enhance the segmentation of the target contours. Finally, we evaluate the proposed DAED-Net on the public MICCAI 2019 StructSeg NPC dataset from different perspectives. Numerical and visual results show that the proposed method outperforms nine state-of-the-art segmentation methods and yields more accurate NPC segmentation results. © 2023 IEEE.

关键词： Convolutional neural network Dual attention Edge detection Nasopharyngeal carcinoma segmentation

来源：评论

学校读者我要写书评

暂无评论

Controlled Cyclic Remote State Preparation of Arbitrary Qubit States

引用

Computers, Materials & Continua 2018年第5期55卷 321-329页

作者： Mingming Wang Chen Yang Reza Mousoli Shanxi Key Laboratory of Clothing Intelligence School of Computer ScienceXi’an Polytechnic UniversityXi’an 710048China State and Local Joint Engineering Research Center for Advanced Networking&Intelligent Information Services School of Computer ScienceXi’an Polytechnic UniversityXi’an 710048China School of Law Criminal Justice and ComputingCanterbury Christ Church UniversityCanterburyKentUK

Quantum secure communications could securely transmit quantum information by using quantum ***,novel applications such as bidirectional and asymmetric quantum protocols have been *** this paper,we propose a new method for generating entanglement which is highly useful for multiparty quantum communications such as teleportation and Remote State Preparation(RSP).As one of its applications,we propose a new type of quantum secure communications,*** RSP *** from a four-party controlled cyclic RSP protocol of one-qubit states,we show that this cyclic protocol can be generalized to a multiparty controlled cyclic RSP protocol for preparation of arbitrary qubit *** point out that previous bidirectional and asymmetric protocols can be regarded as a simpler form of our cyclic RSP protocols.

关键词： Quantum secure communications remote state preparation cyclic communications asymmetric communications bidirectional communications quantum control.

来源：评论

学校读者我要写书评

暂无评论

Relay selections for cooperative underlay CR systems with energy harvesting

Relay selections for cooperative underlay CR systems with en...

引用

作者： Ye, Jia Liu, Zhedong Zhao, Hui Pan, Gaofeng Ni, Qiang Alouini, Mohamed-Slim Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing400715 China Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia School of Computing and Communications Lancaster University LancasterLA1 4WA United Kingdom

In this paper, we consider a cooperative underlay cognitive radio system in which one secondary user (S) transmits its data to a secondary receiver with the assistance of multiple relays. In the considered underlay spectrum sharing scenario, the transmit power levers at S and forwarding relays are adjusted simultaneously according to a given threshold interference power that the primary user can tolerate. We also consider that relays adopt threshold decode-and-forward relay scheme and harvest energy from the primary transmitter with finite energy storage capacity under time switching scheme. Three best relay selection (RS) schemes, optimal source-relay link with wireless energy harvesting (WEH), optimal relay-destination link with WEH and optimal source-relay-destination link with WEH schemes, are proposed and studied. Closed-form analytical expressions for the outage probability of these three best RS schemes are derived, respectively. Finally, our analytical results are verified by Monte-Carlo simulations. © 2015 IEEE.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network

引用

IEEE Transactions on Multimedia 2024年 27卷 2256-2267页

作者： Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Yang, Jian Qi, Guo-Jun Lin, Chia-Wen Beijing University of Posts and Telecommunications Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing100080 China Shanghai University School of Communication and Information Engineering Shanghai200444 China Nanjing University of Posts and Telecommunications Intelligent Visual Information Perception Laboratory Institute of Advanced Technology Nanjing210046 China Ministry of Education Key Laboratory of Artificial Intelligence Shanghai200240 China Soochow University Provincial Key Laboratory for Computer Information Processing Technology Suzhou215006 China Nanjing University of Science and Technology School of Computer Science and Technology Nanjing210094 China Westlake University Research Center for Industries of the Future School of Engineering Hangzhou310024 China OPPO Research SeattleWA98101 United States National Tsing Hua University Department of Electrical Engineering Institute of Communications Engneering Hsinchu300044 Taiwan

Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss of middle-layer features due to activation functions. To minimize the impact of intermediate feature loss on reconstruction quality, we propose a Feature Interaction Weighted Hybrid Network (FIWHN), which comprises a series of Wide-residual Distillation Interaction Block (WDIB) as the backbone. Every third WDIB forms a Feature Shuffle Weighted Group (FSWG) by applying mutual information shuffle and fusion. Moreover, to mitigate the negative effects of intermediate feature loss, we introduce Wide Residual Weighting units within WDIB. These units effectively fuse features of varying levels of detail through a Wide-residual Distillation Connection (WRDC) and a Self-Calibrating Fusion (SCF). To compensate for global feature deficiencies, we incorporate a Transformer and explore a novel architecture to combine CNN and Transformer. We show that our FIWHN achieves a favorable balance between performance and efficiency through extensive experiments on low-level and high-level tasks. Codes will be available at https://***/IVIPLab/FIWHN. © 1999-2012 IEEE.

关键词： Transformers Convolutional neural networks Computational modeling Feature extraction Training Superresolution Adaptation models Computer architecture Telecommunications Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Segmentation of HGG and LGG MRI Images Using WFL-Based 3D U-Net

引用

Journal of Biomedical Science and Engineering 2022年第10期15卷 241-260页

作者： Ahliddin Shomirov Jing Zhang Mohammad Masum Billah School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan China

The semantic segmentation of a brain tumor is the essential stage in medical treatment planning. Due to the different characteristics of tumors, one of the main difficulties in image segmentation is the severe imbalance between classes. Also, a dataset with imbalanced classes is a common problem in multimodal 3D brain MRIs. Despite these problems, most studies in brain tumor segmentation are biased toward the overrepresented tumor class (majority class) and ignore the small size tumor class (minority class). In this paper, we propose an improved loss function Weighted Focal Loss (WFL), based on 3D U-Net to enhance the prediction of brain tumor segmentation. Using our proposed loss function (WFL) solves the imbalance between classes and the imbalance between weights by giving higher weights to the minority and lower weights to the majority. After assigning these weights to different pixel values, our work is able to resolve pixel degradation, which is one of the limitations of the loss function during model training. Based on our experiments, the proposed function (WFL) on the 3D U-Net model for high-grade glioma (HGG) and low-grade glioma (LGG) in the Brain Tumor Segmentation Challenge (BraTS) 2019 dataset has shown promising results for tumor core (TC), whole tumor (WT) and enhanced tumor (ET) with average dice scores of HGG: 0.830, 0.913, 0.815 and Dice scores of LGG for TC: 0.731, WT: 0.775 and ET: 0.685. Moreover, we deployed our training on BraTS 2020 in which we obtained mean Dice scores of HGG: TC: 0.843, WT: 0.892, ET: 0.871 and Dice scores of LGG: 0.7501, 0.7985, 0.6103 for TC, WT and ET, respectively.

关键词： Brain Tumor Segmentation 3D U-Net WFL HGG and LGG

来源：评论

学校读者我要写书评

暂无评论

Combat data shift in few-shot learning with knowledge graph

引用

Frontiers of Computer Science 2023年第1期17卷 101-111页

作者： Yongchun ZHU Fuzhen ZHUANG Xiangliang ZHANG Zhiyuan QI Zhiping SHI Juan CAO Qing HE Key Lab of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Institute of Artificial Intelligence Beihang UniversityBeijing 100191China Xiamen Institute of Data Intelligence Xiamen 361021China Computer Science and Engineering University of Notre DameIN 46556USA University of California San Diego La JollaCA 92093USA College of Information Engineering&Academy for Multidisciplinary Studies Capital Normal UniversityBeijing 100089China

Many few-shot learning approaches have been designed under the meta-learning framework, which learns from a variety of learning tasks and generalizes to new tasks. These meta-learning approaches achieve the expected performance in the scenario where all samples are drawn from the same distributions (i.i.d. observations). However, in real-world applications, few-shot learning paradigm often suffers from data shift, i.e., samples in different tasks, even in the same task, could be drawn from various data distributions. Most existing few-shot learning approaches are not designed with the consideration of data shift, and thus show downgraded performance when data distribution shifts. However, it is non-trivial to address the data shift problem in few-shot learning, due to the limited number of labeled samples in each task. Targeting at addressing this problem, we propose a novel metric-based meta-learning framework to extract task-specific representations and task-shared representations with the help of knowledge graph. The data shift within/between tasks can thus be combated by the combination of task-shared and task-specific representations. The proposed model is evaluated on popular benchmarks and two constructed new challenging datasets. The evaluation results demonstrate its remarkable performance.

关键词： few-shot data shift knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Quantum codes derived from symmetric designs

引用

Journal of Computational information Systems 2012年第17期8卷 7155-7162页

作者： Qian, Jianfa College of Science Anhui University of Science and Technology Huainan 232007 China Science Computing and Intelligent Information Processing of Guangxi Higher Education Key Laboratory Guangxi Teachers Education University Nanning 530023 China

Most of quantum codes have been constructed by using classical linear codes over finite field. However, little is known about the construction of quantum codes from symmetric designs. In this work, we present the constructions of quantum codes and asymmetric quantum codes based on symmetric designs, and give explicit parameters for infinite families of quantum codes and asymmetric quantum codes. © 2012 Binary information Press.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

RALT—A film review sentiment classification model

RALT—A film review sentiment classification model

引用

International Conference on Computer Engineering and Applications (ICCEA)

作者： Ning Chen Xiangzhen He Xianghe Meng Yugang Dai Key Laboratory of Linguistic and Cultural Computing Ministry of Education (Northwest Minzu University) Lanzhou China Key Laboratory of Minzu Languages and Cultures Intelligent Information Processing Gansu Province (Northwest Minzu University) Lanzhou China

ISBN: (数字)9798350386776

ISBN: (纸本)9798350386783

With the development of the internet and film industry, filmgoers have published a large amount of review texts in many areas such as film analysis, film sharing, and social media. The interpretation of review texts is diverse and strongly environmentally dependent, which adds more difficulty to the task of text classification. How to quickly and accurately judge the sentiment tendency of review texts and classify them accurately, and improve the application value of review text data has become one of the popular research directions in natural language processing (NLP). This article proposes a film review sentiment analysis model RALT, which combines a text convolutional neural network (TextCNN) with a self-attention mechanism and a fused long short-term memory (LSTM). The model uses the RoBERTa Employing a pre-trained model to produce dynamic textual word embeddings addresses the intricacies associated with polysemy. Sentiment classification experiments were conducted on the IMDB dataset. The experiments were conducted by comparing BERT and RoBERTa with TextCNN, RNN, LSTM, BI-LSTM and other models, and it was found that the proposed model achieved the best accuracy and F1-score in the classification *** experiment showed that the model is suitable for the field of film review sentiment classification.

关键词： Accuracy Reviews Social networking (online) Computational modeling Text categorization Feature extraction Data models

来源：评论

学校读者我要写书评

暂无评论

Circularly polarized annular slit antenna based on metasurface

Circularly polarized annular slit antenna based on metasurfa...

引用

International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Jingyang Wang Bo Wu Liang Zhang Xianliang Wu Yue Ma Ruikang Wang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Anhui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal University He-fei China

ISBN: (纸本)9781665482271

In this paper, a circularly polarized annular slit antenna with a center frequency of 2.15 GHz realized through a metasurface was designed. The metasurface is made up of 5×5 periodic units. The impedance bandwidth of annular slit antenna is 2.08-2.5 GHz and after loading the metasurface the frequency range in which the axis ratio of the antenna is less than 3dB is 2.12-2.18 GHz and the gain reaches 3.5 dBi. The linear polarization antenna can be directly converted into circular polarization antenna by loading the metasurface. Reserch show that antenna loaded with metasurface can be widely used in electronic communication field.

关键词： Microwave antennas Polarization Simulation Loading Millimeter wave technology Bandwidth Metasurfaces

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：