检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

1,747 篇 会议
77 册 图书
45 篇 期刊文献

馆藏范围

1,869 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,271 篇 工学
- 1,023 篇 计算机科学与技术...
- 621 篇 软件工程
- 212 篇 光学工程
- 205 篇 电气工程
- 198 篇 信息与通信工程
- 138 篇 生物医学工程（可授...
- 136 篇 生物工程
- 122 篇 控制科学与工程
- 51 篇 机械工程
- 48 篇 电子科学与技术（可...
- 40 篇 化学工程与技术
- 36 篇 仪器科学与技术
- 22 篇 安全科学与工程
- 19 篇 建筑学
- 19 篇 土木工程
- 17 篇 动力工程及工程热...
- 15 篇 材料科学与工程（可...
691 篇 理学
- 350 篇 数学
- 277 篇 物理学
- 190 篇 生物学
- 108 篇 统计学（可授理学、...
- 44 篇 化学
- 30 篇 系统科学
176 篇 管理学
- 113 篇 图书情报与档案管...
- 74 篇 管理科学与工程(可...
- 21 篇 工商管理
117 篇 医学
- 90 篇 临床医学
- 55 篇 基础医学(可授医学...
- 26 篇 药学(可授医学、理...
27 篇 法学
- 26 篇 社会学
17 篇 农学
12 篇 教育学
7 篇 经济学
7 篇 军事学
5 篇 艺术学
4 篇 文学

主题

426 篇 pattern recognit...
191 篇 pattern recognit...
70 篇 artificial intel...
65 篇 feature extracti...
48 篇 neural networks
42 篇 pattern matching
35 篇 face recognition
35 篇 data mining
35 篇 computer imaging...
33 篇 local binary pat...
31 篇 bioinformatics
27 篇 support vector m...
25 篇 image analysis
24 篇 image processing
24 篇 character recogn...
23 篇 image segmentati...
22 篇 deep learning
22 篇 machine learning
22 篇 image recognitio...
21 篇 pattern classifi...

机构

18 篇 national laborat...
8 篇 chinese acad sci...
6 篇 tsinghua univers...
5 篇 indian statistic...
5 篇 pattern recognit...
5 篇 university of ch...
4 篇 department of co...
4 篇 rehabil inst chi...
4 篇 school of comput...
4 篇 concordia univ c...
4 篇 shanghai jiao to...
4 篇 university of so...
3 篇 centre for patte...
3 篇 univ chinese aca...
3 篇 institute of ima...
3 篇 southwest jiaoto...
3 篇 pattern recognit...
3 篇 chinese acad sci...
3 篇 school of comput...
3 篇 institute for pa...

作者

16 篇 suen ching y.
11 篇 xu bo
8 篇 caelli terry
8 篇 tan tieniu
8 篇 yang jie
7 篇 levi j. hargrove
6 篇 hargrove levi j.
6 篇 zhao jun
6 篇 jain anil k.
6 篇 sun zhenan
6 篇 suen cy
6 篇 ney hermann
6 篇 kropatsch walter...
6 篇 huang taiyi
5 篇 zhou jie
5 篇 de-shuang huang
5 篇 liu cheng-lin
5 篇 zong chengqing
5 篇 oommen b.j.
5 篇 ablameyko s.

语言

1,847 篇 英文
18 篇 其他
5 篇 中文

检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics"

共 1869 条记录，以下是251-260 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Face Forgery Detection Algorithm Based on Improved MobileViT Network

Face Forgery Detection Algorithm Based on Improved MobileViT...

引用

6th international conference on Intelligent Computing and Signal Processing (ICSP)

作者： Tiantian Wang Xiaoqi Lu School of Information Engineering Inner Mongolia University of Science and Technology Baotou China Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Baotou China Institute of Information Engineering Inner Mongolia University of Technology Hohhot China

DeepFakes blur the boundaries between reality and forgery, resulting in the collapse of exiting credit system, causing immeasurable consequences for national security and social order. through analysis of existing face forgery techniques, it is found that most generation techniques rely on random noise distribution, and global information will be lost after up sampling. therefore, we propose a deepfake detection algorithm based on improved MobileViT, which uses CNN local space biasing and the global space representation of the Transformer network to learn the local features and global representation of forged faces, respectively. Coordinate attention is introduced to obtain directional perception and position sensitive information, making the model locate synthetic traces of fake faces better and fusion local and global representation more effectively. For the improved generalization of the model, with the GELU activation function to solve the problem of neuron death. Our model achieved 96.2% on FF++(C23) datasets, and 93.7%,94.1%,96.3%,87.9% on DF, F2F, FS, and NT datasets, respectively. Comparing with previous methods, our model has shown detection robustness and better generalization.

关键词：

来源：评论

学校读者我要写书评

暂无评论

pattern recognition approach to Predict Renewable Energy Consumption 6

Pattern Recognition approach to Predict Renewable Energy Con...

引用

6th international Multi-Topic ICT conference, IMTIC 2021

作者： Gulraiz, Asif Zaidi, Syed Sajjad Haider Samad, Abdul National University of Science and Technology Department of Electronics and Power Engineering Islamabad Pakistan Istanbul Technical University Electrical Engineering Department Istanbul Turkey

ISBN: (纸本)9781665482943

the microgrid has been presented in recent years to meet energy requirements as a complementary option. the micro grid comprises of renewable generation, energy storage units and demand management via the low-voltage distribution network, which are part of the intelligent grid implementation. Renewable energy resources, including solar and wind energy, are now used worldwide because of the quick technological progress and environmental benefits. However, it is important to integrate renewable production in the micro grid in advance, for this reason, future power generation from renewable sources must now be predicted. Predicting future energy generation will be helpful in finding requirement for grid integration. Forecasting is the ability to determine periods of stable generation from renewable sources. In this paper a renewable energy generation is predicted which is comprised of solar and wind energy to know the requirements for energy in future. With the help of these results Grid will be configured well in advance to fulfill electricity generation requirements from renewable energy resources. ANN (Artificial Neural Network) and ARMA (Auto-Regressive Moving Average) models are used for prediction of different energy resources. Raw data is first processed using feature extraction technique and then it is used in ANN and ARMA modelling. © 2021 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

UAV Signal Classification Methods Design Based on Neural Network Encoder

UAV Signal Classification Methods Design Based on Neural Net...

引用

international conference on Communications, Information System and Computer Engineering (CISCE)

作者： Jingyin Liu Liya Dou College of Information Science and Technology Beijing University of Chemical Technology Beijing P.R. China

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

Unmanned Aerial Vehicles (UAVs) are becoming increasingly prevalent in various sectors such as healthcare, agriculture, environmental monitoring, disaster management, and more. Consequently, there arises a critical need to develop a robust system capable of accurately discerning UAV signals in complex environments. this paper intends to present a novel UAV signal recognition system predicated on the classification of signals emitted by both the UAV itself and its controller. Leveraging the Wavelet transform, this system extracts pertinent features, subsequently employing a neural network encoder to differentiate between UAV signals and controller signals, as well as distinguishing among various UAV and controller models. the proposed model adopts an autoencoder architecture and introduces innovative enhancements in two key frameworks. the initial framework integrates skip connections within residual layers, thereby ensuring the preservation of essential information during convolutional operations. Simultaneously, the second framework harnesses this retained information to extract supplementary features, thereby enhancing the capability of the model to discern intricate patterns within the data. this amalgamation of the two key frameworks in the proposed model facilitates a more profound comprehension of the embedded feature information, and thereby enhances the efficiency of the system. the proposed model has achieved remarkable results in the experiments of UAV signal classification task, indicating that the optimization of neural network structure in this model is effective for RF signal processing.

关键词： Wavelet transforms Computational modeling Neural networks RF signals pattern classification Medical services Autonomous aerial vehicles

来源：评论

学校读者我要写书评

暂无评论

Toward Fully Exploiting Heterogeneous Corpus: A Decoupled Named Entity recognition Model with Two-stage Training

<i>Toward Fully Exploiting Heterogeneous Corpus</i>: A Decou...

引用

Joint conference of 59th Annual Meeting of the Association-for-Computational-Linguistics (ACL) / 11th international Joint conference on Natural Language Processing (IJCNLP) / 6th Workshop on Representation Learning for NLP (RepL4NLP)

作者： Hu, Yun Zhu, Yeshuang Zhang, Jinchao Zheng, Changwen Zhou, Jie Chinese Acad Sci Inst Software Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Tencent Inc Pattern Recognit Ctr WeChat Shenzhen Peoples R China

ISBN: (纸本)9781954085541

Named Entity recognition (NER) is a fundamental and widely used task in natural language processing (NLP), which is generally trained on the human-annotated corpus. However, data annotation is costly and time-consuming, which restricts its scale and further leads to the performance bottleneck of NER models. In reality, we can conveniently collect large-scale entity dictionaries and distantly supervised data. However, the collected dictionaries are lack of semantic context and the distantly supervised training instances contain large noise, which will bring uncertain effects to NER models when directly incorporated into the high-quality training set. To address the above issue, we propose a BERT-based decoupled NER model with two-stage training to appropriately take advantage of the heterogeneous corpus, including dictionaries, distantly supervised instances, and human-annotated instances. Our decoupled model consists of a Mention-BERT and a Context-BERT to respectively learn from the context-deficient dictionaries and noised distantly supervised instances at the pre-training stage. At the unifiedtraining stage, the two BERTs are trained together on human-annotated data to predict the correct labels for candidate regions. Empirical studies on three Chinese NER datasets demonstrate that our method achieves significant improvements against several baselines, establishing the new state-of-the-art performance.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Automated Make and Model Identification of Reverse Shoulder Implants Using Deep Learning Methodology 6th

Automated Make and Model Identification of Reverse Shoulder ...

引用

6th international conference on Recent Trends in Image Processing and pattern recognition, RTIP2R 2023

作者： Dubey, Ved Prakash Ramanathan, A. Rajagopalan, Senthilvelan Malathy, C. Gayathri, M. Batta, Vineet Kamineni, Srinath School of Computing SRM Institute of Science and Technology Chennai India Department of Orthopaedics MIOT International Hospital Chennai India Department of Orthopaedics and Trauma Luton and Dunstable University Hospital NHS Trust Luton United Kingdom Department of Orthopaedic Surgery and Sports Medicine Elbow Shoulder Research Center University of Kentucky UK HealthCare LexingtonKY United States

ISBN: (纸本)9783031530845

Identification of an Orthopaedic Implant before a revision surgery is very important. Failure to identify an implant causes surgical planning delays, inability to plan for the correct equipment requirements, and can result in poorer patient outcomes. this paper proposes a framework to identify, make and model of two different reverse shoulder implants from X-ray images using Deep Learning Techniques. Both Anterior Posterior and Lateral views of X-rays were used in the study and a comparison was made to identify which view enables better results in identification. Various pre-trained deep learning models such as VGG16, VGG19 and InceptionV3 were used for classification of implants. the proposed methodology identifies both the make and model of the implant with an accuracy of 95% using both Anterior Posterior and Lateral Views and an accuracy of 86.67% using only the Anterior view. © 2024, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Target-Oriented Fine-tuning for Zero-Resource Named Entity recognition

Target-Oriented Fine-tuning for Zero-Resource Named Entity R...

引用

作者： Zhang, Ying Meng, Fandong Chen, Yufeng Xu, Jinan Zhou, Jie Beijing Jiaotong Univ Beijing Key Lab Traff Data Anal & Min Beijing Peoples R China Tencent Inc Pattern Recognit Ctr WeChat AI Shenzhen Peoples R China

ISBN: (纸本)9781954085541

Zero-resource named entity recognition (NER) severely suffers from data scarcity in a specific domain or language. Most studies on zero-resource NER transfer knowledge from various data by fine-tuning on different auxiliary tasks. However, how to properly select training data and fine-tuning tasks is still an open problem. In this paper, we tackle the problem by transferring knowledge from three aspects, i.e., domain, language and task, and strengthening connections among them. Specifically, we propose four practical guidelines to guide knowledge transfer and task finetuning. Based on these guidelines, we design a target-oriented fine-tuning (TOF) framework to exploit various data from three aspects in a unified training manner. Experimental results on six benchmarks show that our method yields consistent improvements over baselines in both cross-domain and cross-lingual scenarios. Particularly, we achieve new state-of-theart performance on five benchmarks.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

A transferable model for pedestrian intention prediction in crosswalks based on mobile phone sensors 22

A transferable model for pedestrian intention prediction in ...

引用

Proceedings of the 2022 6th international conference on Electronic Information Technology and Computer Engineering

作者： Xinyu Wang Xikai Wang Sijing Guo School of Automotive Engineering Wuhan University of Technology China

ISBN: (纸本)9781450397148

To accommodate the path planning of autonomous vehicle (AV), many researchers utilize on-board sensors to predict pedestrians’ intention, but the on-board sensors cannot detect occluded pedestrians. Roadside sensors can solve this problem, but with a high cost if deployed at every crosswalk. Hence, this paper aims at utilizing mobile phone sensors to predict the pedestrians’ intentions at crosswalks. A transferable prediction model is built in the paper, with a purpose of saving the expense of hardware and data collection. that is, the model trained by the pedestrians’ data at one crosswalk can provide high accuracy at other crosswalks, via extracting the features associating the geometric structure of the crosswalks and the pedestrians’ motion data. Various algorithms were applied to build the prediction model, and results showed that the prediction accuracy exceeds 90% in non-transfer task, 80% in normal transfer tasks, with a distance of 5 meters ahead of crossing.

关键词： Mobile phone Pedestrian protection Machine learning pattern recognition V2X Pedestrian intention prediction

来源：评论

学校读者我要写书评

暂无评论

6th EAI international conference on IoT as a Service, IoTaaS 2020

6th EAI International Conference on IoT as a Service, IoTaaS...

引用

6th EAI international conference on IoT as a Service, IoTaaS 2020

ISBN: (纸本)9783030675134

the proceedings contain 63 papers. the special focus in this conference is on IoT as a Service. the topics include: Double-threshold-Based Massive Random Access Protocol for Heterogeneous MTC Networks;IP Addressing and Address Management of Space-Based Network Based on Geographical Division;a Convolutional Neural Network Approach for Stratigraphic Interface Detection;a Deep Neural Network Based Feature Learning Method for Well Log Interpretation;trust Prediction Model Based on Deep Learning in Social Internet of things;An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person;the Intelligent Routing Control Strategy Based on Deep Learning;distributed Opportunistic Channel Access with Optimal Single Relay Under Delay Constraints;Distributed Opportunistic Channel Access Under Single-Bit CSI Feedback;Spectrum Allocation Algorithm for Energy-Constrained UAV in Interweave Cognitive IoT Network Based on Satellite Coverage;Resource Allocation for Multi-UAV Assisted Energy-Efficient IoT Communications with Co-channel Interference;Edge Network Extension Based on Multi-domains Fusion and LEO Satellite;completion of Marine Wireless Sensor Monitoring Data Based on Tensor Mode-n Rank and Tucker Operator;Belief Propagation-Based Joint Iterative Detection and Decoding Algorithm for Asynchronous IDMA Satellite Systems;modulation pattern recognition Based on Wavelet Approximate Coefficient Entropy;a New Message Passing Algorithm Based on Sphere Decoding Improvement;a Novel Codebook Design Scheme for Sparse Code Multiple Access;Multi-view Polarization HRRP Target recognition Based on Convolutional Neural Network;Millimeter-Wave Communications with Beamforming for UAV-Assisted Railway Monitoring System;Improved Pulse Shaping Algorithm for Reducing PAPR in OFDM System;satellite Navigation Software Receiver Design;preface.

关键词：

来源：评论

学校读者我要写书评

暂无评论

6th international conference on Human Centered Computing, HCC 2020

6th International Conference on Human Centered Computing, HC...

引用

6th international conference on Human Centered Computing, HCC 2020

ISBN: (纸本)9783030706258

the proceedings contain 49 papers. the special focus in this conference is on Human Centered Computing. the topics include: A K-means Clustering Optimization Algorithm for Spatiotemporal Trajectory Data;temporal and Spatial Changes of Ecosystem Health in Guangdong Province in Recent 11 Years;salient Attention Model and Classes Imbalance Remission for Video Anomaly Analysis with Weak Label;a Data Fusion Model Based on Multi-source Non-real-Time Intelligence;Ancient Chinese Lexicon Construction Based on Unsupervised Algorithm of Minimum Entropy and CBDB Optimization;Availability Analysis of GNSS RAIM Based on Maximum Undetectable Position Bias;psychological Semantic Differences of Zhang Juzheng Before and After DuoQing Event;digital Rights Management Platform Based on Blockchain Technology;a Deep Hybrid Neural Network Forecasting for Multivariate Non-stationary Time Series;Design of Aquatic Product Traceability Coding Scheme Based on EPC Label;Risk Assessment of Flood Disasters in Hechi City Based on GIS;Cultural Symbol recognition Algorithm Based on CTPN + CRNN;Spatial-Temporal Variation and Future Changing Trend of NDVI in the Pearl River Basin from 1982 to 2015;an Improved Collaborative Filtering Algorithm Based on Filling Missing Data;Diagnosis Method of Alzheimer’s Disease in PET Image Based on CNN Multi-mode Network;research on Multi-floor Path Planning Based on Recommendation Factors;E-commerce Review Classification Based on SVM;experimental Research of Galfenol Composite Cantilever;a Capacitive Flexible Tactile Sensor;multi-objective Optimization of E-commerce Logistics Warehouse Layout Based on Genetic Algorithm;DEVS-Based Modeling and Simulation of Wireless Sensor Network;magnetic Circuit Design of Galfenol Composite Cantilever;micro-video Learning Resource Portrait and Its Application.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Road Tracking in Semi-structured Environments Using Spatial Distribution of Lidar Data 25th

Road Tracking in Semi-structured Environments Using Spatial ...

引用

25th international conference on pattern recognition Workshops, ICPR 2020

作者： Tsiakas, Kosmas Kostavelis, Ioannis Giakoumis, Dimitrios Tzovaras, Dimitrios 6th Km Harilaou -Thermi Road Thessaloniki57100 Greece

ISBN: (纸本)9783030687861

the future civilian, and professional autonomous vehicles to be realised into the market should apprehend and interpret the road in a manner similar to the human drivers. In structured urban environments where signs, road lanes and markers are well defined and ordered, landmark-based road tracking and localisation has significantly progressed during the last decade with many autonomous vehicles to make their debut into the market. However, in semi-structured and rural environments where traffic infrastructure is deficient, the autonomous driving is hindered by significant challenges. the paper at hand presents a Lidar-based method for road boundaries detection suitable for a service robot operation in rural and semi-structured environments. Organised Lidar data undergo a spatial distribution processing method to isolate road limits in a forward looking horizon ahead of the robot. Stereo SLAM is performed to register subsequent road limits and RANSAC is applied to identify edges that correspond to road segments. In addition, the robot traversable path is estimated and progressively merged with Bézier curves to create a smooth trajectory that respects vehicle kinematics. Experiments have been conducted on data collected from our robot on a semi-structured urban environment, while the method has also been evaluated on KITTI dataset exhibiting remarkable performance. © 2021, Springer Nature Switzerland AG.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共187页 << < 22 23 24 25 26 27 28 29 30 31 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：