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

15,854 篇 会议
360 篇 期刊文献
193 册 图书

馆藏范围

16,407 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,314 篇 工学
- 5,413 篇 计算机科学与技术...
- 2,985 篇 软件工程
- 2,163 篇 电气工程
- 1,860 篇 信息与通信工程
- 1,123 篇 控制科学与工程
- 880 篇 光学工程
- 644 篇 机械工程
- 637 篇 电子科学与技术（可...
- 539 篇 生物医学工程（可授...
- 538 篇 仪器科学与技术
- 477 篇 生物工程
- 225 篇 测绘科学与技术
- 217 篇 交通运输工程
- 201 篇 材料科学与工程（可...
- 199 篇 航空宇航科学与技...
- 163 篇 化学工程与技术
- 159 篇 网络空间安全
- 140 篇 安全科学与工程
4,005 篇 理学
- 2,390 篇 物理学
- 1,355 篇 数学
- 527 篇 生物学
- 367 篇 统计学（可授理学、...
- 341 篇 系统科学
- 205 篇 化学
1,521 篇 医学
- 1,348 篇 临床医学
- 200 篇 特种医学
- 197 篇 基础医学(可授医学...
1,054 篇 管理学
- 612 篇 管理科学与工程(可...
- 481 篇 图书情报与档案管...
- 139 篇 工商管理
84 篇 法学
66 篇 农学
45 篇 经济学
43 篇 教育学
37 篇 军事学
32 篇 文学
26 篇 艺术学
1 篇 哲学

主题

2,779 篇 image processing
1,551 篇 image segmentati...
1,513 篇 signal processin...
867 篇 feature extracti...
656 篇 image edge detec...
634 篇 cameras
633 篇 signal processin...
609 篇 real-time system...
575 篇 image reconstruc...
517 篇 image coding
498 篇 algorithm design...
399 篇 clustering algor...
398 篇 deep learning
398 篇 image color anal...
381 篇 object detection
369 篇 image enhancemen...
354 篇 accuracy
334 篇 hardware
323 篇 image analysis
312 篇 computer vision

机构

39 篇 xi'an jiaotong u...
32 篇 northwestern pol...
31 篇 xi an jiao tong ...
31 篇 school of electr...
29 篇 school of electr...
26 篇 university of ch...
24 篇 xi an jiao tong ...
23 篇 national laborat...
22 篇 xi an jiao tong ...
21 篇 signal and image...
19 篇 samara national ...
18 篇 xidian universit...
16 篇 school of inform...
16 篇 institute of art...
15 篇 department of el...
15 篇 school of automa...
15 篇 national key lab...
15 篇 school of comput...
14 篇 tsinghua univers...
14 篇 school of electr...

作者

39 篇 chen xi
29 篇 xi chen
24 篇 nanning zheng
24 篇 licheng jiao
20 篇 li xi
20 篇 liu ying
18 篇 xuelong li
17 篇 anon
14 篇 xi ning
14 篇 wei li
14 篇 yuan yuan
14 篇 xi li
13 篇 de-shuang huang
13 篇 yanning zhang
12 篇 jie yang
12 篇 yang xi
12 篇 ying liu
11 篇 p. pirsch
11 篇 liu yang
11 篇 mingyi he

语言

16,103 篇 英文
159 篇 其他
132 篇 中文
20 篇 土耳其文
3 篇 葡萄牙文
2 篇 法文
2 篇 俄文
1 篇 西班牙文

检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16407 条记录，以下是741-750 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：

Under-Display ToF Imaging with Efficient Transformer

Under-Display ToF Imaging with Efficient Transformer

引用

2023 IEEE International conference on Visual Communications and image processing, VCIP 2023

作者： Sun, Yuan Wei, Hao Qiao, xin Deng, Pengchao Ge, Chenyang Xi'An Jiaotong University Institute of Artificial Intelligence and Robotics China

ISBN: (纸本)9798350359855

Demand for full screen in consumer electronics has propelled the development of under-display image processing. For time-of-flight cameras, they are usually placed under TOLED display. Due to the presence of pixels and display patterns in the TOLED panel, depth maps from under-display time-of-flight (UD-ToF) are noisy, blurry, and inaccurate. We propose a non-local method based on Vision Transformer for UD-ToF depth restoration to address these issues. Specifically, a novel feature attention block is designed to incorporate non-local depth features. Additionally, we take ToF raw measurements rather than the depth map as input, allowing the network to extract informative features from the raw domain. We conduct comprehensive experiments on real RUD-TOF and synthetic SUD-TOF benchmark datasets, and the results indicate that the proposed transformer-based method achieves better performance than the state-of-The-Art algorithms. © 2023 IEEE.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

The Discursive Construction of Organizational Identity of Multinational Enterprise in Different Stages of Internationalization 4

The Discursive Construction of Organizational Identity of Mu...

引用

4th International conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Zizhen, Geng Ziqiong, Qiao Xueting, Sun Nana, Wu Yanfen, Wang Xi' An International Studies University Business School Xi'an China University of Science and Technology of China School of Management Hefei China

ISBN: (纸本)9798350300093

This study investigates the identity construction of Alibaba in different stages of internationalization. First of all, this study uses Python to collect the leadership speeches of Alibaba in the process of internationalization from its official website. Secondly, this study applies the natural language processing (NLP) of Python to make high-frequency word statistics and the word cloud picture of leadership speeches. Finally, based on the textual data collected by Python, this study adopts the Discourse-Historical Approach (DHA) to analyze the identity construction of Alibaba in the process of internationalization. The results demonstrated that (1) in the first stage of internationalization, Alibaba focuses on building an amiable corporate image, and (2) in the second stage of internationalization, Alibaba pays attention to construct a selfless corporate image. By exploring and comparing the identity construction of Alibaba in the different stages of internationalization, this study, on the one hand, could furnish some helpful reference with other multinational enterprises to build an appropriate corporate image in the process of expanding overseas markets, on the other hand, could enrich the research perspective and method of organization identity construction. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Research on Feature Fusion Methods for Multimodal Medical Data 38th

Research on Feature Fusion Methods for Multimodal Medical Da...

引用

38th CCF National conference of Computer Applications, CCF NCCA 2023

作者： Xu, Zhaogang Yang, xi Jin, Yu Chen, Shuyu Chongqing University Chongqing400044 China

ISBN: (纸本)9789819987634

With the rapid development of artificial intelligence, knowledge graph, image processing, etc. have been widely used, and smart medical care, as a major application scenario of artificial intelligence, has received a lot of attention. Traditional diagnostic methods have problems such as low accuracy and low efficiency, and the research and application of knowledge graph and image classification in the field of dermatology are also in the initial stage, but text-based knowledge graph technology and image-based image classification technology have developed very maturely. Considering that various current image classification algorithms extract features, feature calculation, and model matching from images, they do not consider obtaining information such as features or relationships that are not in images from text data to participate in image classification tasks. In this paper, the optimized hierarchical perception model H-HAKE based on hierarchical perception model KGE-HAKE calculates selector parameters by improving the hierarchical perception model to add category dimension to the TransE coordinate system, divide more image features and entities with the same attribute into the same level, increase the number of links between image and map entities, and produce better data coverage effect. Aiming at the image classification task, this paper proposes a game tree model to optimize the classification results, including calculating the confidence degree based on the map, the aggregation degree of the classification results, the inference value of the entities in the domain, etc., and comprehensively designing the fusion mode of knowledge graph and image classification algorithm KG-based CNN in scenarios such as multi-map input and feature pre-extraction. The mode is effective enough to enable the image classification task to utilize multimodal data, and the effectiveness is verified by multi-scenario and data ablation experiments on the public data collection. © 2024,

关键词： image classification

来源：评论

学校读者我要写书评

暂无评论

image Filtering and Edge Detection System Based on FPGA 10th

Image Filtering and Edge Detection System Based on FPGA

引用

10th International conference on Communications, Signal processing, and systems

作者： Sun xiaodong Wang Zhiqiang Jing Wei Dalian Neusoft Univ Informat Sch Intelligence & Elect Engn Dalian 116023 Peoples R China

ISBN: (纸本)9789811903908;9789811903892

The edge of the feature image contains rich data information, which is an important feature information of the image. The real-time display of the image is required in the actual system. In this paper, a real-time image filtering and edge detection system is designed by using Gaussian filtering and Sobel edge detection algorithm. The system is implemented on FPGA. According to the processing flow of image acquisition, image processing and image display, the function of real-time image display on the screen is realized. The image display effect under different threshold settings is compared, and the appropriate threshold settings are proposed.

关键词： FPGA image processing Edge detection algorithms Gauss filtering

来源：评论

学校读者我要写书评

暂无评论

Frame-Adaptive Multi-Object Tracking for Discontinuous image Sequences 2

Frame-Adaptive Multi-Object Tracking for Discontinuous Image...

引用

2nd International conference on Algorithm, image processing and Machine Vision, AIPMV 2024

作者： Li, xiaolei xiao, xingjie Yang, Siyuan Sha, Moquan Sha, Zongyao Tu, Jianguang School of Remote Sensing and Information Engineering Wuhan University Wuhan China Wuhan Luojia Zhongheng Remote Sensing Data Technology Co Wuhan China China Unicom Smart City Research Institute Beijing China

ISBN: (纸本)9798350390254

In the field of multi-object tracking, this study introduces an innovative framework designed to address the challenges posed by frame loss in image sequences, particularly within the contexts of video surveillance and traffic management. Despite the significant achievements of deep learning-based tracking methods in processing high frame rate videos, frame loss remains a prevalent issue in real-world deployments due to network and hardware constraints, which can result in erroneous target associations and interrupted trajectory tracking. Our research begins by detecting frame loss through a timestamp- based analysis, this is followed by the deployment of an adaptive algorithm that fuses spatial and appearance metrics to compensate for the positional discrepancies and visual inconsistencies caused by missing frames, thus improving the precision of data association. We have curated a dataset that accurately reflects real-world environments, and conducted validation on subsampled versions of the MOT17 and MOT20 datasets, in addition to our original dataset. Empirical results indicate that our multi-object tracking approach demonstrates significant adaptability and robustness in handling discontinuous image sequences, reducing the number of ID switches by 54.1 % on our original dataset compared to state-of-the-art methods. The proposed framework has the potential to significantly enhance the performance of multi-object tracking systems in real-world scenarios where frame loss is a common occurrence, thereby improving the reliability and accuracy of video surveillance and traffic management applications. © 2024 IEEE.

关键词： Adaptive algorithms

来源：评论

学校读者我要写书评

暂无评论

3rd International conference on Optimization, Learning algorithms and Applications, OL2A 2023

3rd International Conference on Optimization, Learning Algor...

引用

3rd International conference on Optimization, Learning algorithms and Applications, OL2A 2023

ISBN: (纸本)9783031530357

The proceedings contain 26 papers. The special focus in this conference is on Optimization, Learning algorithms and Applications. The topics include: Pest Detection in Olive Groves Using YOLOv7 and YOLOv8 Models;Using LiDAR Data as image for AI to Recognize Objects in the Mobile Robot Operational Environment;an Evaluation of image Preprocessing in Skin Lesions Detection;an Artificial Intelligence-Based Method to Identify the Stage of Maturation in Olive Oil Mills;vehicle Industry Big Data Analysis Using Clustering Approaches;enhancing Forest Fire Detection and Monitoring Through Satellite image Recognition: A Comparative Analysis of Classification algorithms Using Sentinel-2 Data;An Efficient GPU Parallelization of the Jaya Optimization Algorithm and Its Application for Solving Large systems of Nonlinear Equations;Multi-objective Optimal Sizing of an AC/DC Grid Connected Microgrid System;sub-system Integration and Health Dashboard for Autonomous Mobile Robots;movement Pattern Recognition in Boxing Using Raw Inertial Measurements;optimization Models for Hydrokinetic Energy Generated Downstream of Hydropower Plants;deep Conditional Measure Quantization;fault Classification of Wind Turbine: A Comparison of Hyperparameter Optimization Methods;Assessing the Reliability of AI-Based Angle Detection for Shoulder and Elbow Rehabilitation;deep Learning and Machine Learning Techniques Applied to Speaker Identification on Small Datasets;performance of Heuristics for Classifying Leftovers from Cutting Stock Problem;Deep Learning-Based Classification and Quantification of Emulsion Droplets: A YOLOv7 Approach;identification of Late Blight in Potato Leaves Using image processing and Machine Learning;adaptive Convolutional Neural Network for Predicting Steering Angle and Acceleration on Autonomous Driving Scenario;Impact of EMG Signal Filters on Machine Learning Model Training: A Comparison with Clustering on Raw Signal;assessing the 3D Position of a Car with a Single 2D Camera Usin

关键词：

来源：评论

学校读者我要写书评

暂无评论

HSO-Based K-Means Segmentation for Identification of Disease and Deficiency in Paddy Plant

HSO-Based K-Means Segmentation for Identification of Disease...

引用

International conference on Advanced Communications and Machine Intelligence, MICA 2023

作者： Sivagami, S. Mulakaluri, Sailaja Saranya, C. Ashtalakshmi, K. Kalpana, R. Manoshankari, M. Department of Computer Science and Applications St. Francis de Sales College Electronic City P.O Bengaluru560 100 India

ISBN: (纸本)9789819762217

In agriculture, image processing is frequently used to identify issues with fruit grading, weed identification, disease diagnosis, and other related tasks. In order to detect nutritional deficiencies and paddy plant disease, this study employs image processing. image has to classified as diseased or nutrient deficient after performing segmentation of image and selection of important features from the image. There are many different image segmentation algorithms available. K-means is an incredibly easy algorithm to understand, apply, and provide accurate results with. Despite its accuracy and simplicity, its drawbacks include the requirement to estimate the value of K and choose K’s initial centroids at random from the provided data values. A unique image segmentation technique was developed to solve this problem. It is based on the identification of inadequacies using K-means and harmonic search optimization (HSO). The K-means algorithm’s performance is significantly impacted by the randomly chosen values for K and the centroid values of the clusters. The standard K-means method takes longer to produce accurate results because it needs random initialization. A K-means method based on HSO is suggested to expedite the initialization procedure. The aim function of the suggested approaches is the Otsu technique with an initial step created from the HSO. The HSO method is used to locate the cluster canters, which are then used to begin the K-means algorithm. Lastly, when segmentation results are compared to those obtained using the fuzzy C-means and classic K-means segmentation algorithms, the recommended HSO-based K-means technique performs better than the rivals. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Indoor Human Detection Based on Convolutional Neural Network and image-based processing

Indoor Human Detection Based on Convolutional Neural Network...

引用

Natural Language processing (ICNLP), International conference on

作者： Junhua Yang Guodong Bai Jingyu Lu Xi’an University of Posts and Telecommunications School of Electronic Engineering Xi’an China

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

Indoor human detection technology is a critical component in the fields of indoor security and smart furniture. The current technology, which is based on Wi-Fi Channel State Information (CSI), relies solely on a single CSI amplitude information, resulting in a less stable human body detection system. To overcome this limitation, this study introduces a novel method, CSI-image processing (CSI-IP), which combines the lightweight convolutional neural network SqueezeNET with the traditional signal processing technology, and integrates CSI amplitude information and phase information. The method involves processing the original phase information and amplitude information using linear transform and wavelet transform, respectively, and constructing CSI amplitude image and phase image. These images are then fused using the Laplace pyramid fusion algorithm, and a convolutional neural network is used to classify and learn the fused image to achieve human body detection. Experimental results in four different environments (laboratory, laboratory corridor, library, and library corridor) show that the detection rate of the algorithm is 0.9264, 0.9416, 0.9068, 0.9464, respectively, which is significantly higher than that of traditional algorithms under the same conditions, demonstrating the effectiveness and stability of the method.

关键词： Wavelet transforms Training Laboratories Signal processing algorithms Signal processing Libraries Classification algorithms Convolutional neural networks Security Wireless fidelity

来源：评论

学校读者我要写书评

暂无评论

Zero-Shot image Classification: Recent Status and Future Trends

Zero-Shot Image Classification: Recent Status and Future Tre...

引用

Natural Language processing (ICNLP), International conference on

作者： xiaodong Feng Ying Liu Tuan Kiang Chiew Center for Image and Information Processing Xi’an University of Posts and Telecommunications Xi’an China Rekindle Pte Ltd Singapore

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

Deep learning has achieved great success in image classification tasks. However, the majority of the methods can only recognize classes that have already appeared in the training set. In practical applications, it is also necessary to recognize classes that have not been appeared in the training set. Zero-shot learning can help to solve this problem. In zero-shot image classification, classes in the training set are entirely different from those used in the test set. This paper provides a systematic study on zero-shot image classification algorithms over the past few years. Firstly, we provide the research background of zero-shot image classification. Secondly, we introduce the basic concepts of various zero-shot image classification methods, including the semantic embedding and extraction of features. Thirdly, we categorize existing zero-shot image classification algorithms into three main groups - direct semantic prediction-based methods, space mapping-based methods, and generative model-based methods. We then analyze and compare their respective performance on three common datasets. Finally, we provide a summary of the technical challenges and future research directions of zero-shot image classification.

关键词： Training Visualization Systematics Zero-shot learning Semantics Predictive models Feature extraction Prediction algorithms Classification algorithms image classification

来源：评论

学校读者我要写书评

暂无评论

SoftPatch: Unsupervised Anomaly Detection with Noisy Data 36

SoftPatch: Unsupervised Anomaly Detection with Noisy Data

引用

36th conference on Neural Information processing systems (NeurIPS)

作者： Jiang, xi Liu, Jianlin Wang, Jinbao Nie, Qian Wu, Kai Liu, Yong Wang, Chengjie Zheng, Feng Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China Tencent Youtu Lab Shenzhen Peoples R China

ISBN: (纸本)9781713871088

Although mainstream unsupervised anomaly detection (AD) algorithms perform well in academic datasets, their performance is limited in practical application due to the ideal experimental setting of clean training data. Training with noisy data is an inevitable problem in real-world anomaly detection but is seldom discussed. This paper considers label-level noise in image sensory anomaly detection for the first time. To solve this problem, we proposed a memory-based unsupervised AD method, SoftPatch, which efficiently denoises the data at the patch level. Noise discriminators are utilized to generate outlier scores for patch-level noise elimination before coreset construction. The scores are then stored in the memory bank to soften the anomaly detection boundary. Compared with existing methods, SoftPatch maintains a strong modeling ability of normal data and alleviates the overconfidence problem in coreset. Comprehensive experiments in various noise scenes demonstrate that SoftPatch outperforms the state-of-the-art AD methods on the MVTecAD and BTAD benchmarks and is comparable to those methods under the setting without noise.

关键词： Anomaly detection

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500页 << < 71 72 73 74 75 76 77 78 79 80 > >>

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：