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

777 篇 会议
5 册 图书
1 篇 期刊文献

馆藏范围

783 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

466 篇 工学
- 404 篇 计算机科学与技术...
- 231 篇 软件工程
- 137 篇 信息与通信工程
- 107 篇 电气工程
- 60 篇 生物医学工程（可授...
- 58 篇 生物工程
- 37 篇 控制科学与工程
- 34 篇 电子科学与技术（可...
- 20 篇 光学工程
- 15 篇 化学工程与技术
- 14 篇 机械工程
- 14 篇 仪器科学与技术
- 12 篇 安全科学与工程
- 11 篇 动力工程及工程热...
- 10 篇 交通运输工程
173 篇 理学
- 91 篇 数学
- 65 篇 生物学
- 43 篇 物理学
- 37 篇 统计学（可授理学、...
- 28 篇 系统科学
- 15 篇 化学
98 篇 管理学
- 63 篇 图书情报与档案管...
- 39 篇 管理科学与工程(可...
- 23 篇 工商管理
63 篇 医学
- 54 篇 临床医学
- 40 篇 基础医学(可授医学...
- 31 篇 药学(可授医学、理...
13 篇 法学
- 12 篇 社会学
13 篇 农学
- 13 篇 作物学
12 篇 教育学
- 12 篇 教育学
8 篇 经济学
1 篇 军事学

主题

207 篇 machine learning
93 篇 signal processin...
87 篇 deep learning
64 篇 signal processin...
62 篇 feature extracti...
56 篇 support vector m...
50 篇 training
49 篇 machine learning...
30 篇 neural networks
21 篇 natural language...
20 篇 image processing
16 篇 computational mo...
14 篇 prediction algor...
13 篇 svm
13 篇 sentiment analys...
13 篇 data models
13 篇 convolutional ne...
12 篇 internet of thin...
12 篇 estimation
11 篇 covid-19

机构

6 篇 college of engin...
6 篇 department of co...
4 篇 xidian universit...
3 篇 department of el...
3 篇 university of du...
3 篇 peng cheng labor...
3 篇 uttaranchal inst...
3 篇 department of el...
3 篇 national laborat...
3 篇 graphic era deem...
2 篇 kl business scho...
2 篇 khulna universit...
2 篇 khulna universit...
2 篇 northwest minzu ...
2 篇 shandong univers...
2 篇 central universi...
2 篇 imt cdl ghaziaba...
2 篇 department of co...
2 篇 school of marine...
2 篇 school of comput...

作者

8 篇 wathiq mansoor
4 篇 yassine himeur
3 篇 alavikunhu panth...
3 篇 li zheng
3 篇 abigail copiaco
3 篇 jing wang
3 篇 joel alanya-belt...
3 篇 rashid ali
3 篇 shadi atalla
3 篇 abbes amira
3 篇 lei huang
2 篇 cheng xinzhou
2 篇 sherin m. yousse...
2 篇 liashchynskyi pe...
2 篇 kumar ashwani
2 篇 sarno riyanarto
2 篇 khawla a. alnajj...
2 篇 chang ming-ching
2 篇 liu ze-guo
2 篇 taleb mohammed

语言

753 篇 英文
27 篇 其他
2 篇 西班牙文
2 篇 中文

检索条件"任意字段=5th International Conference on Signal Processing and Machine Learning, SPML 2022"

共 783 条记录，以下是561-570 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：

Estimate Height Weight and Body Mass Index From Face Image Using machine learning

Estimate Height Weight and Body Mass Index From Face Image U...

引用

international conference on Multimedia, signal processing and Communication Technologies, (IMPACT)

作者： Ashwani Kumar Kondam Deeksha G. Sai Pooja T. Tarun Reddy Tera Akhil Reddy SRM Institute of Science and Technology NCR Campus Ghaziabad Sreyas Institute of Engineering and Technology Hyderabad India

ISBN: (纸本)9781665476485

Human body photographs contain encodings for gender, weight, and other biometric data in addition to pupil color. When considering all of this information, body weight is a reliable indicator of health problems. Body measurements including height, weight, and body mass index (BMI) are important because they can be used for a variety of purposes like surveillance, re-identification, picture retrieval systems, and healthcare. the majority of earlier research on automated height, weight, and BMI measurement has made use of 3D whole body videos and 2D and full body 2D pictures. A person's weight in proportion to their height is gauged by their BMI. It serves more as a gauge for calculating total body fat. Because it is frequently used to evaluate health issues, BMI is important. Our chances of living a longer, healthier life are said to be increased by having a healthy body mass index (BMI).the BMI range may be identified and classified using picture analysis, which can help individuals forecast credibility, manage their BMI, and lead healthier lives. there hasn't been much discussion on face estimation. Being overweight has been linked to obesity, diabetes, and cardiovascular disease. Weight is also an important health indicator. Using the methods Linear Regression, Ridge Linear Regression, Random Forest Regressor, and Kernel Ridge Regression, CNN algorithm, and Resnet-50 Architecture, we test the feasibility of estimating height, weight, and BMI from single-shot face photos. In order to estimate height, weight, and BMI, we will evaluate these regression models and select the one with the highest test score.

关键词： Weight measurement three-dimensional displays Surveillance Linear regression Feature extraction Indexes Kernel

来源：评论

学校读者我要写书评

暂无评论

Research on Raman fiber amplifier using neural network combining PSO algorithm 22

Research on Raman fiber amplifier using neural network combi...

引用

Proceedings of the 2022 5th international conference on Artificial Intelligence and Pattern Recognition

作者： jiamin Gong Jiaojiao Lu Ruijie Gao Xi'an University of Posts & Telecommunications Xi'an University of Posts & Telecommunications China

ISBN: (纸本)9781450396899

We propose an efficient hybrid method that combines neural network and particle swarm optimization algorithm to optimize the performance of backward multi-pumped Raman fiber amplifiers. We use a neural network to inverse system design Raman fiber amplifier by learning the nonlinear mapping relationship between pump light and the output gain. To obtain a flat gain spectrum, the particle swarm optimization algorithm is used to search for the optimal pump slight parameter configuration. the results show that when the designed Raman amplifier is oriented toward C+L band signal optical amplification, the error between the target gain value and the actual gain value is less than 0.47 dB, the output gain after optimization is 17.96dB, and the gain flatness is 0.44dB.

关键词： Inverse design machine learning Neural network Optical communication Raman fiber amplifier

来源：评论

学校读者我要写书评

暂无评论

Sound Source Localization Method Based on Densely Connected Convolutional Neural Network

Sound Source Localization Method Based on Densely Connected ...

引用

IEEE international conference on Information Communication and signal processing (ICICSP)

作者： Ge Zhang Lin Geng Xingguo Chen School of Electrical Engineering and Automation Anhui University Hefei China

Beamforming and deconvolution techniques play a significant role in identifying sound sources. However, it is commonly known that conventional beamforming (CBF) is difficult to identify sound sources accurately due to its inherent drawbacks, including low spatial resolution and small dynamic ranges, while deconvolution methods are burdened with huge computational costs and fail to provide reliable results. Aiming to overcome the restrictions of conventional beamforming and deconvolution methods, a novel sound source localization method combining conventional beamforming with a deep learning method is proposed. In this paper, the sound source localization task is framed as an image prediction task. Firstly, conventional beamforming (CBF) is utilized for obtaining the initial sound source spatial distribution maps. Secondly, a target map is designed as the ground truth label for training. then a densely connected convolutional neural network (DCFCN) with an encoder-decoder structure is established for extracting features from CBF maps and predicting the spatial distribution of a single sound source. Finally, the position of a single sound source can be retrieved from the predicted maps generated by DCFCN. Simulations are carried out to verify the effectiveness of the proposed method by comparing it with several traditional sound source localization methods. Results suggest that the proposed method can not only significantly improve the spatial resolution and dynamic range of CBF but also achieve accurate localization with high computational efficiency.

关键词： Location awareness Graphical models Deconvolution Array signal processing Dynamic range Feature extraction Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Pedestrian Trajectory Prediction Based on Improved Social Spatio-Temporal Graph Convolution Neural Network 22

Pedestrian Trajectory Prediction Based on Improved Social Sp...

引用

Proceedings of the 2022 5th international conference on machine learning and Natural Language processing

作者： Jikun Yang Chao Han School of Electrical Engineering Anhui Polytechnic University China

ISBN: (纸本)9781450399067

Pedestrian trajectory prediction is a key technology in the field of autonomous driving. the trajectory of pedestrians is not only affected by the surrounding objects, but also by the social interaction between adjacent pedestrians. Aiming at the problem that pedestrian interaction visual blind area is easy to be ignored in pedestrian trajectory prediction, a convolution network algorithm based on spatio-temporal graph is proposed. Firstly, Pedestrian feature information is obtained by spatio-temporal graph. then the connection weights between irrelevant points are screened out according to the visual blind area. Finally, the time extrapolation convolution neural network (TXP-CNN) is used to predict the future trajectory of pedestrians. through experiments on two public datasets (Eth and UCY), average displacement error (ADE) and the final displacement error (FDE) of the proposed model on the dataset are 0.42 and 0.73, respectively.

关键词： machine vision trajectory prediction blind area screening double Gaussian distribution time-extrapolator convolution neural network

来源：评论

学校读者我要写书评

暂无评论

Development of 2D Indoor Monitoring and Positioning System (IMPS) Using Received signal Strength Indicator (RSSI) Assisted by Internet of things (IoT) 11th

Development of 2D Indoor Monitoring and Positioning System (...

引用

11th international conference on Robotics, Vision, signal processing and Power Applications, RoViSP 2021

作者： Wahab, Nur Haliza Abdul Ariffin, Sharifah Hafizah Syed Latiff, Liza Radzi, Raja Zahilah Raja Mohd Wessam, H. Aaina Saleh, N. School of Computing Faculty of Engineering Universiti Teknologi Malaysia Skudai Malaysia School of Electrical Engineering Faculty of Engineering Universiti Teknologi Malaysia Skudai Malaysia Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Skudai Malaysia School of Mechanical Engineering Faculty of Engineering Universiti Teknologi Malaysia Skudai Malaysia

ISBN: (纸本)9789811681288

As humans, nearly eighty percent of our day-to-day activities are conducted in an indoor environment, making indoor tracking and monitoring extremely necessary. the needs of having an Indoor Positioning System (IPS) has become crucial as the development is critically challenged due to the fact that satellite signals via Global Positioning System (GPS) cannot penetrate through a building. Variety techniques and approaches on IPS have been proposed but the most desirable approach used is the Received signal Strength Indicator (RSSI) due to existing infrastructure already in place to provide a low-cost implementation. Internet of things (IoT) itself has brought drastic changes and opened new opportunities for growth and innovation in technology. An integration between RSSI and IoT is the perfect combination of the development of IPS to allow an increased accuracy. this paper proposes an Indoor Monitoring and Positioning System (IMPS) using RSSI algorithm and triangulation technique integrated with IoT. the experimental results show that the proposed IMPS has achieved an average accuracy of 0.5 m for 2D. Future work has suggested an improvement in the IMPS with AR mapping integrated with machine learning. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

A method for presenting biomedical images based on a model of receptive fields of human visual perception 5

A method for presenting biomedical images based on a model o...

引用

5th international Scientific conference on Information, Control, and Communication Technologies, ICCT 2021

作者： Antsiperov, V.E. Kershner, V.A. Kotelnikov Institute of Radioengineering and Electronics of Russian Academy of Sciences 11 Mokhovaya street building 7 Moscow125009 Russia

the paper is devoted to the development of a new method for presenting biomedical images based on local characteristics of the intensity of their shape. the proposed method of image processing is focused on images that have low indicators of the intensity of the recorded radiation, resolution, contrast and signal-to-noise ratio. the method is based on the principles of machine (Bayesian) learning and on samples of random photo reports. this paper presents the results of the method and its connection with modern approaches in the field of image processing. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Image processing

来源：评论

学校读者我要写书评

暂无评论

SigT: An Efficient End-to-End MIMO-OFDM Receiver Framework Based on Transformer

SigT: An Efficient End-to-End MIMO-OFDM Receiver Framework B...

引用

international conference on Communications, signal processing, and their Applications (ICCSPA)

作者： Ziyou Ren Nan Cheng Ruijin Sun Xiucheng Wang Ning Lu Wenchao Xu School of Telecommunications Engineering Xidian University Xi'an China Department of Electrical and Computer Engineering Queen's University Kingston Ontario Canada Department of Computing The Hong Kong Polytechnic University Hongkong China

ISBN: (纸本)9781665482387

Multiple-input multiple-output and orthogonal frequency-division multiplexing (MIMO-OFDM) are the key technologies in 4G and subsequent wireless communication systems. Conventionally, the MIMO-OFDM receiver is performed by multiple cascaded blocks with different functions and the algorithm in each block is designed based on ideal assumptions of wireless channel distributions. However, these assumptions may fail in practical complex wireless environments. the deep learning (DL) method has the ability to capture key features from complex and huge data. In this paper, a novel end-to-end MIMO-OFDM receiver framework based on transformer, named SigT, is proposed. By regarding the signal received from each antenna as a token of the transformer, the spatial correlation of different antennas can be learned and the critical zero-shot problem can be mitigated. Furthermore, the proposed SigT framework can work well without the inserted pilots, which improves the useful data transmission efficiency. Experiment results show that SigT achieves much higher performance in terms of signal recovery accuracy than benchmark methods, even in a low SNR environment or with a small number of training samples. Code is available at https://***/SigTransformer/SigT.

关键词： Wireless communication Training Adaptation models Correlation Receiving antennas Benchmark testing signal processing

来源：评论

学校读者我要写书评

暂无评论

Instrument Fault Diagnosis Method based on machine learning

Instrument Fault Diagnosis Method based on Machine Learning

引用

IEEE international conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Hainuo Wang Yangsen Liu Yucong Zhang Zhiyuan Wang Yingzhe Shao Xin Zhang Lin Tang Jiayu Chen Chongqing University of Posts and Telecommunications Chongqing China University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781665471978

ISBN: (纸本)9781665471985

this paper mainly through the analysis of instrument waveform signal data, extract important signal characteristics, and then achieve intelligent fault detection of equipment and instruments. According to the characteristics of signal data, we firstly draw boxplot, de-noise outliers, extract principal component features with principal component analysis (PCA), extract important features with random forest algorithm, and then use K-means clustering algorithm and Gaussian mixture distribution to classify equipment faults. Finally, Random forest and its optimization and Gauss-naive Bayes method are used to classify equipment faults.

关键词： machine learning algorithms Instruments Clustering algorithms Predictive models Feature extraction Data models Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Applications of machine learning to Skin Cancer Detection

Applications of Machine Learning to Skin Cancer Detection

引用

international conference on Contemporary Computing and Informatics (IC3I)

作者： Anju J. Prakash Gargibala Satpathy Ramakrishnan Raman E. Manikandan Dharam Buddhi Dhiraj Kapila Department of CSE Sree Buddha College of Engineering Pattoor Alappuzha Department of Biotechnology Sree Balaji Medical College and Hospital (SBMCH) Bharath Institute of Higher Education and Research Chrompet Chennai India Symbiosis Institute of Business Management Pune & Symbiosis International (Deemed University) Pune Maharashtra India Department of Physics TUCAS Campus Solid-State Nanoscale Laboratory Thiruvalluvar University Thennangur Vellore India Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India Department of Computer Science & Engineering Lovely Professional University Phagwara Punjab India

Owing to shortage of awareness regarding signs and measures for prophylaxis, skin cancer (SC), among the most severe kinds of carcinoma (Ca), is actively destroying far more people than it used to. Consequently, in order to halt the progression of Ca, timely identification during an early phase is crucial. Melanoma, baseline-cell, as well as squamous cellular Ca are the deadliest subtypes of SC. Under this research, distinct SC kinds will be identified and classified utilizing machine learning and image processing techniques. Dermoscopy imaging are taken into consideration as input during the pre-processing phase. All undesirable hairs on skin lesion are removed using dull razor technique, and the picture is then smoothed using a Gaussian filtering. Median filter is employed to reduce noisiness and protect lesion’s borders. Colour-based k-means grouping is carried out in the segmentation process because colour is a key element in determining the kind of malignancy. With the help of Asymmetric, Boundary, Colour, Diameter (ABCD) and Gray Level Cooccurrence (GLC) matrix, statistic and textural retraction of features is carried out. the ISIC 2019 datasets, which consists of 8 distinct kinds of dermoscopy pictures, is used for investigation conducted. Multi-class Support Vector machine (SVM) was used for classifying with an accurateness of roughly 96.25 percent.

关键词： Support vector machines Hair Image color analysis Medical treatment Imaging machine learning Melanoma

来源：评论

学校读者我要写书评

暂无评论

An Innovative Internet Of things (IoT) Computing-Based Health Monitoring System With the Aid of machine learning Approach

An Innovative Internet Of Things (IoT) Computing-Based Healt...

引用

international conference on Contemporary Computing and Informatics (IC3I)

作者： Bhupendra Kumar Namita Rajput Nagesh Yagnam Department of Accounting & Finance College of Business & Economics Debre Tabor University Debre Tabor Ethiopia Department of Commerce Sri Aurobindo College University of Delhi Delhi India Department of Information & Technology Debre Tabor University Ethiopia Africa

the community health area comprises a massive amount of information, and particular approaches are used to handle that information. One of the most common approaches is handling as well as processing. this technique forecasts the likely consequences of cardiovascular disease. the outcome of this method is to predict the preceding heart illness. the job controls IOT using a sensor (a pulse sensor to monitor pulses) and Arduino, and the results may be seen on a sequential screen. IFTTT is used to analyze sensor readings in Google Sheets, which are subsequently converted into CSV go-like data. the datasets used are classified according to treatment parameters, in addition to being used for data preparation and testing. this technique evaluates those parameters using the information preparation order method. With AI computations and categorization work. the dataset is first dissected, examined, and screened, after which the gathered data is processed in Python programming using machine learning Algorithms, namely Decision Tree Algorithm with Random Backwoods Classification Algorithm. SVM (Support vector machine) produces the best results in terms of detecting heart disease. As a result, the suggested paradigm is shown to be a reliable one for predicting past heart disease. the suggested hardware and software technology assists patients in predicting cardiac disease in its initial stages.

关键词： Temperature measurement Temperature sensors Heart Support vector machines Wireless communication Wireless sensor networks machine learning algorithms

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79页 << < 53 54 55 56 57 58 59 60 61 62 > >>

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：