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

78,696 篇 会议
791 篇 期刊文献
327 册 图书
2 篇 学位论文

馆藏范围

79,816 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

49,790 篇 工学
- 29,026 篇 计算机科学与技术...
- 23,038 篇 电气工程
- 16,840 篇 软件工程
- 16,488 篇 信息与通信工程
- 5,193 篇 电子科学与技术（可...
- 4,842 篇 光学工程
- 4,529 篇 控制科学与工程
- 3,424 篇 生物医学工程（可授...
- 3,097 篇 机械工程
- 2,823 篇 仪器科学与技术
- 2,034 篇 生物工程
- 700 篇 化学工程与技术
- 560 篇 材料科学与工程（可...
- 517 篇 动力工程及工程热...
- 515 篇 航空宇航科学与技...
- 496 篇 交通运输工程
- 484 篇 安全科学与工程
- 473 篇 网络空间安全
19,855 篇 理学
- 12,170 篇 物理学
- 7,863 篇 数学
- 2,310 篇 生物学
- 2,213 篇 统计学（可授理学、...
- 1,567 篇 系统科学
- 860 篇 化学
10,889 篇 医学
- 10,412 篇 临床医学
- 1,076 篇 基础医学(可授医学...
- 1,035 篇 特种医学
- 694 篇 药学(可授医学、理...
3,228 篇 管理学
- 2,001 篇 管理科学与工程(可...
- 1,353 篇 图书情报与档案管...
392 篇 农学
350 篇 法学
287 篇 军事学
177 篇 经济学
119 篇 教育学
117 篇 文学
67 篇 艺术学

主题

7,222 篇 image processing
6,649 篇 signal processin...
5,263 篇 image coding
5,026 篇 image segmentati...
4,066 篇 image reconstruc...
3,852 篇 signal processin...
3,198 篇 feature extracti...
2,239 篇 image analysis
1,993 篇 digital signal p...
1,708 篇 robustness
1,688 篇 image edge detec...
1,680 篇 cameras
1,647 篇 training
1,614 篇 deep learning
1,588 篇 speech processin...
1,462 篇 pixel
1,422 篇 image resolution
1,382 篇 image enhancemen...
1,332 篇 image color anal...
1,186 篇 visualization

机构

53 篇 university of sc...
49 篇 univ chinese aca...
41 篇 department of si...
40 篇 institute for in...
40 篇 shanghai jiao to...
39 篇 tsinghua univers...
38 篇 school of electr...
38 篇 shanghai jiao to...
36 篇 national institu...
36 篇 school of comput...
34 篇 princeton univ d...
34 篇 beijing inst tec...
33 篇 ibm thomas j. wa...
33 篇 shenzhen interna...
30 篇 institute of inf...
30 篇 beijing key labo...
28 篇 zhejiang univers...
27 篇 nanyang technol ...
27 篇 centre for multi...
27 篇 astar inst infoc...

作者

51 篇 zhang lei
46 篇 wiegand thomas
40 篇 yang bin
33 篇 jie yang
32 篇 jing zhang
32 篇 kaup andre
31 篇 m. vetterli
29 篇 vetterli martin
29 篇 m. gabbouj
28 篇 li li
27 篇 guangtao zhai
27 篇 li xin
27 篇 wang jing
26 篇 karam lina j.
25 篇 jian wang
24 篇 zhang tao
24 篇 m.j.t. smith
24 篇 li yang
24 篇 jun wang
23 篇 kuo c. -c. jay

语言

77,952 篇 英文
1,057 篇 其他
503 篇 土耳其文
289 篇 中文
9 篇 俄文
5 篇 西班牙文
2 篇 法文
1 篇 葡萄牙文

检索条件"任意字段=IEEE International Conference on Signal and Image Processing Applications"

共 79816 条记录，以下是4571-4580 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：

AI Based Fundus image classification Using Bayesian Classifier 10

AI Based Fundus Image classification Using Bayesian Classifi...

引用

10th international conference on Communication and signal processing, ICCSP 2024

作者： Utikar, Arti Bongulwar, Milind Patil, C.Y. Coep Technological University Instrumentation & Control Engg Pune India Govt. Coe Instrumentation & Control Engg Pune Awasari India

ISBN: (纸本)9798350353068

Diabetic Retinopathy is a degenerative ocular condition resulting from elevated levels of insulin in the bloodstream, which, if not promptly identified, may lead to vision loss. Figure 1 displays the primary components of digital retinal pictures used for the automated identification of diabetic retinopathy (DR), including blood vessels, optic disc, macula, and fovea[1]. Since the retina is a vascular structure, any alteration in the structure of the retina or blood vessels indicates an abnormality. Therefore, these primary components may be used to identify the existence of any lesion in the retina. Early-stage screening of Fundus images is crucial to prevent additional damage to the retina. Prompt diagnosis of Proliferative Diabetic Retinopathy (PDR)[6] is of utmost significance and may be achieved by precise identification of blood vessels. The retinal picture may be taken from four different perspectives: (1) Posterior - towards the middle and front, (2) Inferior - towards the higher and front, (3) Superior - towards the lower and front, and (4) Temporal - towards the side. These perspectives may be used to determine the precise position of PDR on the retina. This programme seeks to identify the perspectives that are impacted. This information is beneficial for doctors when recommending laser therapy to their patients. © 2024 ieee.

关键词： Blood vessels

来源：评论

学校读者我要写书评

暂无评论

Magnetic Resonance image Analysis: A Healthcare System 4

Magnetic Resonance Image Analysis: A Healthcare System

引用

4th ieee international conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Dubey, Shivendra Singh, Shweta Dubey, Sakshi Nair, Rajit Sharma, Rahul Manipal University School of Engineering Department of Computer Science and Engineering Department of Aiml Rajasthan Jaipur India Jagran Lakecity University School of Engineering and Technology Madhya Pradesh Bhopal India Rkdf University Department of Electronics and Communication Madhya Pradesh Bhopal India Vit Bhopal University Department of Computer Science and Engineering Madhya Pradesh Bhopal India Parul Institute of Technology Parul University Department of Computer Science and Engineering Gujarat Vadodara India

ISBN: (纸本)9798331518981

In today's medical image, analyses are captured very rapidly due to early detection of the brain tumour being very important. The tumour could be plainly visible in the neurological magnetic resonance imaging study, but the doctor must also quantify the tumour area at a certain level in order to conduct additional research. Machine learning has witnessed remarkable consideration over the past few years. From the analysis of medical images to natural language processing, several machine learning models spanning many fields appear to be able to detect tumours and are widely used in applications in academia, business, and medical science. These advancements have a significant impact on healthcare in a broad range of areas, including healthcare, medical imaging technologies, medical diagnostics, and medical data analysis. We give a broad summary of current developments in machine learning used for medical processing and evaluation of images as well as related difficulties. Magnetic Resonance image (MRI) analysis using IoT involves collecting data from connected medical devices and sensors to create MRI images. Machine learning algorithms can then be used to analyze this data in order to find trends and forecast the health of patients. It can assist medical professionals in making better decisions that will enhance patient care and outcomes. © 2024 ieee.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Radar Based Humans Localization with Compressed Sensing and Sparse Reconstruction 24

Radar Based Humans Localization with Compressed Sensing and ...

引用

24th international conference on Digital signal processing, DSP 2023

作者： Eckrich, Christian Schroth, Christian A. Jamali, Vahid Zoubir, Abdelhak M. Signal Processing Group Resilient Communication Systems Technische Universität Darmstadt Germany

ISBN: (纸本)9798350339598

Localization and detection is a vital task in emergency rescue operations. Devastating natural disasters can create environments that are inaccessible or dangerous for human rescuers. Contaminated areas or buildings in danger of collapsing can be searched by rescue robots which are equipped with diverse sensors such as optical and radar sensors. In scenarios where the line of sight is blocked, e.g., by a wall, a door or heavy smoke or dust, sensors like LiDAR or cameras are not able to provide sufficient information. The usage of radar in these kinds of situations can drastically improve situational awareness and hence the likelihood of rescue. In this paper, we present a method that is used for radar imaging behind obstacles by utilizing a signal model that includes the floor reflection propagation path in addition to the direct path of the radar signal. Additionally, compressed sensing methods are presented and applied to real world radar data that was recorded by a Stepped Frequency Continuous Wave (SFCW) radar mounted on a semi-autonomous robot. The results show an improved radar image that allows the clear identification of persons behind obstacles. © 2023 ieee.

关键词： Radar imaging

来源：评论

学校读者我要写书评

暂无评论

EYES TELL ALL: IRREGULAR PUPIL SHAPES REVEAL GAN-GENERATED FACES 47

EYES TELL ALL: IRREGULAR PUPIL SHAPES REVEAL GAN-GENERATED F...

引用

47th ieee international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Guo, Hui Hu, Shu Wang, Xin Chang, Ming-Ching Lyu, Siwei SUNY Albany Albany NY 12222 USA Univ Buffalo State Univ New York Buffalo NY USA Keya Med Seattle WA USA

ISBN: (纸本)9781665405409

Generative adversarial network (GAN) generated high-realistic human faces are visually challenging to discern from real ones. They have been used as profile images for fake social media accounts, which leads to high negative social impacts. In this work, we show that GAN-generated faces can be exposed via irregular pupil shapes. This phenomenon is caused by the lack of physiological constraints in the GAN models. We demonstrate that such artifacts exist widely in high-quality GAN-generated faces. We design an automatic method to segment the pupils from the eyes and analyze their shapes to distinguish GAN-generated faces from real ones. Qualitative and quantitative evaluations of our method on the Flickr-Faces-HQ dataset and a StyleGAN2 generated face dataset demonstrate the effectiveness and simplicity of our method.

关键词： image forensics GAN faces detection pupil segmentation fake face detection

来源：评论

学校读者我要写书评

暂无评论

TRANSFORM SKIP INSPIRED END-TO-END COMPRESSION FOR SCREEN CONTENT image 29

TRANSFORM SKIP INSPIRED END-TO-END COMPRESSION FOR SCREEN CO...

引用

ieee international conference on image processing (ICIP)

作者： Wang, Meng Zhang, Kai Zhang, Li Wu, Yaojun Li, Yue Li, Junru Wang, Shiqi City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Bytedance Inc San Diego CA 92122 USA Beijing Bytedance Technol Co Ltd Beijing Peoples R China

ISBN: (数字)9781665496209

ISBN: (纸本)9781665496209

Existing end-to-end image compression mainly concentrates on the coding of natural scene images. However, few works have been dedicated to the end-to-end compression of screen contents. In this paper, we propose an end-to-end compression scheme for screen content images inspired by the ideology of transform skip, with the goal of improving the compression performance for screen content images. In particular, the proposed model takes full consideration of the characteristics of screen contents and involves transform skip branches to the analyses and synthesis process. The transform skip branch equips with coarse feature extraction and reconstruction. As such, the visual signals could be more briefly interpreted at the encoder-side and recovered at the decoder-side. Experimental results show that the proposed method outperforms the existing hyperprior-based model for screen content compression, achieving 10.16% BD-Rate savings in high bit-rate coding scenario and 5.38% BD-Rate savings in low bit-rate coding scenario.

关键词： End-to-end compression screen content compression transform skip hyperprior model

来源：评论

学校读者我要写书评

暂无评论

Study on CPU and FPGA in Artificial Intelligence and Machine Learning 13

Study on CPU and FPGA in Artificial Intelligence and Machine...

引用

13th international conference of Information and Communication Technology, ICTech 2024

作者： Zhou, Peng School of Electrical and Computer Engineering Nang Fang College Guangzhou China

ISBN: (纸本)9798350376258

—This article provides a comprehensive examination of the roles played by Central processing Units (CPUs) and Field-Programmable Gate Arrays (FPGAs) in the realms of Artificial Intelligence (AI) and Machine Learning (ML), with a particular emphasis on the superiorities of FPGA over CPU in certain aspects. It is observed that CPUs, while versatile, fall short in aspects such as power efficiency, handling the intricacies of deep learning models, and performing large-scale matrix computations. FPGAs, on the other hand, are lauded for their remarkable flexibility, low latency, superior energy efficiency, and inherent parallelism — qualities that are immensely beneficial in AI and ML applications. The article delves into the real-world applications of both CPUs and FPGAs, showcasing specific scenarios where each excels. For instance, the low latency advantage of FPGAs is crucial in image processing tasks, where quick, efficient processing can be pivotal. In contrast, CPUs are better suited for smaller-scale or general-purpose computing tasks where flexibility and ease of programming are key. This contrast highlights the nuanced roles that these technologies play in the broader context of AI and ML. Further, the article contrasts CPUs and FPGAs in terms of architecture, design philosophy, and suitability for various AI and ML workloads. While CPUs offer a general-purpose solution with a well-established ecosystem, FPGAs provide a customizable platform that can be tailored to specific needs, offering a more efficient solution for certain types of computational tasks in AI and ML. This comparison not only sheds light on the inherent strengths and weaknesses of each technology but also underscores the importance of choosing the right tool for specific AI and ML applications, thereby optimizing performance, efficiency, and power consumption. ©2024 ieee.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

STSANet: Retinal Vessel Segmentation via Spatial-Temporal and Self-Attention Encoding 14

STSANet: Retinal Vessel Segmentation via Spatial-Temporal an...

引用

14th ieee international conference on Wireless Communications and signal processing (WCSP)

作者： Huang, Yi Deng, Tao Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu Peoples R China

ISBN: (纸本)9781665450850

Retinal vessel segmentation can improve the judgment ability of intelligent disease diagnosis system. Although a large number of retinal vessel segmentation models have been proposed with the development of deep learning, it is still a challenging task. In this work, we propose a new retinal vessel segmentation network via spatial-temporal and self-attention encoding modules, called STSANet, which can significantly improve the performance and robustness of segmentation. The spatial-temporal information of fundus images are extracted by a Spatial-Temporal encoding module in the STSANet. In addition, the internal correlation of features is captured by the Self-Attention module. By fusing spatial-temporal and self-attention features, the final result contains both spatial-temporal information and internal feature information of fundus images. The experimental results indicate that our STSANet outperforms other state-of-the-art retinal segmentation models on the published standard datasets.

关键词： Fundus image Vessel segmentation Spatial-temporal encoding Self-Attention

来源：评论

学校读者我要写书评

暂无评论

SOLVING THE LONG-TAILED PROBLEM VIA INTRA- AND INTER-CATEGORY BALANCE 47

SOLVING THE LONG-TAILED PROBLEM VIA INTRA- AND INTER-CATEGOR...

引用

47th ieee international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Zhang, Renhui Lin, Tiancheng Zhang, Rui Xu, Yi Shanghai Jiao Tong Univ Shanghai Peoples R China

ISBN: (纸本)9781665405409

Benchmark datasets for visual recognition assume that data is uniformly distributed, while real-world datasets obey long-tailed distribution. Current approaches handle the long-tailed problem to transform the long-tailed dataset to uniform distribution by re-sampling or re-weighting strategies. These approaches emphasize the tail classes but ignore the hard examples in head classes, which result in performance degradation. In this paper, we propose a novel gradient harmonized mechanism with category-wise adaptive precision to decouple the difficulty and sample size imbalance in the long-tailed problem, which arc correspondingly solved via intra- and inter-category balance strategies. Specifically, infra-category balance focuses on the hard examples in each category to optimize the decision boundary, while inter-category balance aims to correct the shift of decision boundary by taking each category as a unit. Extensive experiments demonstrate that the proposed method consistently outperforms other approaches on all the datasets.

关键词： long-tailed distribution image classification adaptive precision gradients harmonizing

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

SAFARI FROM VISUAL signalS: RECOVERING VOLUMETRIC 3D SHAPES 47

SAFARI FROM VISUAL SIGNALS: RECOVERING VOLUMETRIC 3D SHAPES

引用

47th ieee international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Agudo, Antonio UPC Inst Robbt & Informat Ind CSIC Barcelona Spain

ISBN: (纸本)9781665405409

In this paper we propose a convex approach for recovering a detailed 3D volumetric geometry of several objects from visual signals. To this end, we first present a minimal detailed surface energy that is optimized together with a volume constraint by considering some geometrical priors, and without requiring neither additional training data nor templates in order to constrain the solution. Our problem can be efficiently solved by means of a gradient descent, and be applied for single RGB images or monocular videos even with very small rigid motions. Temporal-aware solutions and driven by point correspondences are incorporated without assuming any 2D tracking data over time. Thanks to this formulation, both rigid and non-rigid objects can be considered. We have extensively validated our approach in a wide variety of scenarios in the wild, recovering challenging type of shapes that have not been previously attempted without assuming any training data.

关键词： Visual signals Mininal Surfaces image and Video Understanding

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 << < 454 455 456 457 458 459 460 461 462 463 > >>

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：