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

12,600 篇 会议
189 篇 期刊文献
161 册 图书

馆藏范围

12,950 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

6,510 篇 工学
- 4,291 篇 计算机科学与技术...
- 2,186 篇 软件工程
- 1,876 篇 电气工程
- 1,291 篇 信息与通信工程
- 840 篇 控制科学与工程
- 652 篇 光学工程
- 463 篇 生物医学工程（可授...
- 441 篇 电子科学与技术（可...
- 437 篇 机械工程
- 427 篇 仪器科学与技术
- 316 篇 生物工程
- 222 篇 测绘科学与技术
- 151 篇 材料科学与工程（可...
- 144 篇 航空宇航科学与技...
- 135 篇 交通运输工程
- 101 篇 安全科学与工程
- 93 篇 网络空间安全
- 84 篇 化学工程与技术
3,128 篇 理学
- 2,086 篇 物理学
- 891 篇 数学
- 357 篇 生物学
- 246 篇 系统科学
- 224 篇 统计学（可授理学、...
- 111 篇 化学
1,434 篇 医学
- 1,272 篇 临床医学
- 193 篇 特种医学
- 157 篇 基础医学(可授医学...
- 99 篇 药学(可授医学、理...
698 篇 管理学
- 426 篇 管理科学与工程(可...
- 293 篇 图书情报与档案管...
59 篇 法学
59 篇 农学
30 篇 教育学
27 篇 文学
26 篇 经济学
17 篇 军事学
15 篇 艺术学
1 篇 哲学

主题

2,662 篇 image processing
1,390 篇 image segmentati...
1,144 篇 signal processin...
609 篇 cameras
607 篇 feature extracti...
585 篇 image edge detec...
521 篇 signal processin...
477 篇 real-time system...
474 篇 image reconstruc...
460 篇 image coding
390 篇 algorithm design...
336 篇 image color anal...
316 篇 deep learning
308 篇 image enhancemen...
304 篇 pixel
300 篇 real time system...
296 篇 object detection
291 篇 computer archite...
286 篇 hardware
284 篇 neural networks

机构

22 篇 signal and image...
19 篇 samara national ...
14 篇 school of electr...
11 篇 samara national ...
11 篇 univ texas san a...
11 篇 department of el...
11 篇 school of electr...
10 篇 center for signa...
9 篇 information syst...
9 篇 institute of ima...
9 篇 tongji universit...
8 篇 university of to...
8 篇 purdue univ sch ...
8 篇 university of ch...
8 篇 electrical compu...
8 篇 image processing...
8 篇 information syst...
8 篇 samara national ...
7 篇 school of electr...
7 篇 department of ma...

作者

19 篇 anon
13 篇 de-shuang huang
13 篇 jagdish chand ba...
11 篇 p. pirsch
10 篇 jie yang
10 篇 panetta karen
10 篇 j.m. mendel
10 篇 r. chellappa
10 篇 a. ortega
9 篇 c.-c.j. kuo
8 篇 frank hannig
8 篇 bovik alan c.
8 篇 hannig frank
8 篇 mahalanobis a
8 篇 ilias maglogiann...
8 篇 carli m.
7 篇 miller jwv
7 篇 busch christoph
7 篇 semenishchev e.
7 篇 zelensky a.

语言

12,254 篇 英文
611 篇 其他
94 篇 中文
19 篇 土耳其文
3 篇 葡萄牙文
2 篇 西班牙文
2 篇 俄文
1 篇 法文

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

共 12950 条记录，以下是811-820 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：

Latency-aware Spatial-wise Dynamic Networks 36

Latency-aware Spatial-wise Dynamic Networks

引用

36th conference on Neural Information processing systems (NeurIPS)

作者： Han, Yizeng Yuan, Zhihang Pu, Yifan Xue, Chenhao Song, Shiji Sun, Guangyu Huang, Gao Tsinghua Univ Dept Automat BNRist Beijing Peoples R China Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China

ISBN: (纸本)9781713871088

Spatial-wise dynamic convolution has become a promising approach to improving the inference efficiency of deep networks. By allocating more computation to the most informative pixels, such an adaptive inference paradigm reduces the spatial redundancy in image features and saves a considerable amount of unnecessary computation. However, the theoretical efficiency achieved by previous methods can hardly translate into a realistic speedup, especially on the multi-core processors (e.g. GPUs). The key challenge is that the existing literature has only focused on designing algorithms with minimal computation, ignoring the fact that the practical latency can also be influenced by scheduling strategies and hardware properties. To bridge the gap between theoretical computation and practical efficiency, we propose a latency-aware spatial-wise dynamic network (LASNet), which performs coarse-grained spatially adaptive inference under the guidance of a novel latency prediction model. The latency prediction model can efficiently estimate the inference latency of dynamic networks by simultaneously considering algorithms, scheduling strategies, and hardware properties. We use the latency predictor to guide both the algorithm design and the scheduling optimization on various hardware platforms. Experiments on image classification, object detection and instance segmentation demonstrate that the proposed framework significantly improves the practical inference efficiency of deep networks. For example, the average latency of a ResNet-101 on the imageNet validation set could be reduced by 36% and 46% on a server GPU (Nvidia Tesla-V100) and an edge device (Nvidia Jetson TX2 GPU) respectively without sacrificing the accuracy. Code is available at https://***/LeapLabTHU/LASNet.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Bacterial Blight and Cotton Leaf Curl Virus Detection Using Inception V4 Based CNN Model for Cotton Crops 5

Bacterial Blight and Cotton Leaf Curl Virus Detection Using ...

引用

5th IEEE International conference on image processing Applications and systems (IPAS)

作者： Anwar, Sohail Kolachi, Abdul Rahim Baloch, Shadi Khan Soomro, Shoaib R. Mehran Univ Engn & Technol Dept Elect Engn Jamshoro Pakistan Mehran Univ Engn & Technol Dept Mechatron Engn Jamshoro Pakistan

ISBN: (纸本)9781665462198

Agriculture sector is an important pillar of the global economy. The cotton crop is considered one of the prominent agricultural resources. It is widely cultivated in India, China, Pakistan, USA, Brazil, and other countries of the world. The worldwide cotton crop production is severely affected by numerous diseases such as cotton leaf curl virus (CLCV/CLCuV), bacterial blight, and ball rot. image processing techniques together with machine learning algorithms are successfully employed in numerous fields and have also used for crop disease detection. In this study, we present a deep learning-based method for classifying diseases of the cotton crop, including bacterial blight and cotton leaf curl virus (CLCV). The dataset of cotton leaves showing disease symptoms is collected from various locations in Sindh, Pakistan. We employ the Inception v4 architecture as a convolutional neural network to identify diseased plant leaves in particular bacterial blight and CLCV. The accuracy of the designed model is 98.26% which shows prominent improvement compared to the existing models and systems.

关键词： cotton crop disease detection CNN CLCV Bacterial Blight detection image processing

来源：评论

学校读者我要写书评

暂无评论

Proceedings - 2023 32nd International conference on Parallel Architecture and Compilation Techniques, PACT 2023

Proceedings - 2023 32nd International Conference on Parallel...

引用

32nd International conference on Parallel Architecture and Compilation Techniques, PACT 2023

ISBN: (纸本)9798350342543

The proceedings contain 33 papers. The topics discussed include: MBAPIS: multi-level behavior analysis guided program interval selection for microarchitecture studies;automatic code generation for high-performance graph algorithms;SimplePIM: a software framework for productive and efficient processing-in-memory;Drishyam: an image is worth a data prefetcher;architecture-aware currying;PreFlush: lightweight hardware prediction mechanism for cache line flush and writeback;retargeting applications for heterogeneous systems with the tribble source-to-source framework;dynamic allocation of processor cores to graph applications on commodity servers;parallelizing maximal clique enumeration on GPUs;and HugeGPT: storing guest page tables on host huge pages to accelerate address translation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

AI Applications in Satellite image processing: Enhancing Earth Observation and Environmental Monitoring 5

AI Applications in Satellite Image Processing: Enhancing Ear...

引用

5th IEEE International conference on Electro-Computing Technologies for Humanity, NIGERCON 2024

作者： Ojo, Olakunle L. Ajiboye, Yinka Afolalu, Adeniran S. Morebise, Ademola T. Omoyajowo, Ifeoluwa M. Abe, Oladipo E. Olumodimu, Olugbenga Adeyeye, David S. Agboola, Olugbenga M. Olawunmi, Oyelami Afe Babalola University Department of Mathematical and Physical Sciences Ado Ekiti Nigeria Afe Babalola University Department of Mathematical & Physical Sciences Ekiti State Ado-Ekiti Nigeria Afe Babalola University Department of Mechanical and Mechatronics Engineering Ado-Ekiti Nigeria University of Johannesburg Department of Mechanical Engineering Science South Africa Afe Babalola University Department of Mathematical and Physical Sciences Ekiti State Ado-Ekiti Nigeria Afe Babalola University Students Affair Unit Ado Ekiti Nigeria Federal University Department of Physics Oye Ekiti Nigeria University of Portsmouth Institute of Cosmology and Gravitation United Kingdom Achievers University Department of Geological Sciences Ondo State Owo Nigeria Afe Babalola University Department of Tourism and Events Management Ado Ekiti Nigeria University of Lagos Geography Department Lagos Nigeria

ISBN: (纸本)9798331542559

Satellite image processing is a cornerstone of modern Earth observation, providing critical data for meteorology, resource management, and urban studies. The integration of artificial intelligence (AI) has significantly enhanced image analysis through machine learning, deep learning, and data fusion techniques, improving efficiency and accuracy. This study examines AI-driven transformations in satellite image processing, focusing on applications in disaster monitoring, urban growth assessment, hyperspectral vegetation analysis, and air quality evaluation. We also explore AI algorithms such as supervised and unsupervised learning models, convolutional neural networks (CNNs), and data fusion techniques, which facilitate complex image interpretation. Additionally, challenges in AI integration with satellite systems are discussed, along with future research directions to advance Earth observation and environmental monitoring. Overall, this review highlights AI's indispensable role in satellite imagery for global decision-making. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Deep Learning Environmental Monitoring Machine Learning Satellite image processing

来源：评论

学校读者我要写书评

暂无评论

2022 International conference on Intelligent systems and Computer Vision, ISCV 2022

2022 International Conference on Intelligent Systems and Com...

引用

5th International conference on Intelligent systems and Computer Vision, ISCV 2022

ISBN: (纸本)9781665495585

The proceedings contain 71 papers. The topics discussed include: a new sampling strategy to improve the performance of mobile robot path planning algorithms;machine learning based methods for Arabic duplicate question detection;robust traffic signs classification using deep convolutional neural network;image-based visual servoing techniques for robot control;SASHA: a shift-add segmented hybrid approximated multiplier for image processing;graph based method for Arabic text summarization;face information forensics analysis based on facial aging: a survey;advanced financial data processing and labeling methods for machine learning;and recognition system of human activities based on time-frequency features of accelerometer data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Vision Transformer based ResNet Model for Pneumonia Prediction 4

Vision Transformer based ResNet Model for Pneumonia Predicti...

引用

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

作者： Sowmya, Thatikonda Sai Narasimhulu, Thumma Sunitha, Gurram Manikanta, Thupakula Venkatesh, Thirupathi Sree Vidyanikethan Engineering College Department of CSE A.P Tirupati India Mohan Babu University School of Computing Department of Ai & Ml A.P Tirupati India

ISBN: (纸本)9798350300093

This research study aims to develop a pneumonia detection system using vision transformers. Pneumonia is a very serious respiratory illness that may result in severe health issues, and early detection is essential for effective treatment. Deep learning-based computer vision algorithms have yielded encouraging results in medical image analysis in recent years, and vision transformers have emerged as a potent tool for processing visual data. The proposed system uses a vision transformer to process chest x-ray images and extract visual traits, which can be utilized for classification. The proposed model 'Vit_base_resnet50_224_in21k' is trained on a vast and diverse dataset of annotated chest x-ray images to understand the patterns and characteristics of pneumonia. The system's performance is estimated using standard evaluation parameters - accuracy, loss, specificity, sensitivity, F1-score and ROC curve. The proposed model has achieved a performance accuracy of 92.96% for pneumonia detection. The results demonstrate the potential of vision transformers in chest x-ray image analysis and contribute to the development of more accurate and efficient tools for pneumonia detection. This system has the potential to assist healthcare professionals in making faster and more accurate diagnosis, which can ultimately improve outcomes and save lives. © 2023 IEEE.

关键词： image analysis

来源：评论

学校读者我要写书评

暂无评论

A New Efficient Split & Merge Algorithm for Embedded systems

A New Efficient Split & Merge Algorithm for Embedded Systems

引用

IEEE International conference on image processing

作者： Nathan Maurice Julien Sopena Lionel Lacassagne LIP6 Sorbonne University Paris

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

This article presents a new image segmentation algorithm based on a Split & Merge approach. By nature, the execution time of Split & Merge algorithms is data-dependent, as their halting conditions are tied to the homogeneity of each region. While previous algorithms made the Split step less sensitive to input data, the execution time of the more complex Merge step remains highly sensitive to image content. This paper tackles the sensitivity and performance problems from a system and architecture perspective. Memory reallocations due to array fusions are eliminated with the introduction of a TTA (Three Table Array) structure in the Merge step. As iterating over entries in this structure causes a loss of memory locality, we propose two new mechanisms that implement a software cache to mitigate this. An experimental study on an embedded system (Nvidia Jetson Xavier NX) has shown our Merge algorithm to be 10.6 times faster than the state-of-the-art Split & Merge algorithm for $960 \times 720$ images. Moreover, the execution time of our algorithm is also more resistant to image characteristics.

关键词： Resistance image segmentation Embedded systems Sensitivity Software algorithms Streaming media Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Face Recognition Implementation Based on image processing Techniques

Face Recognition Implementation Based on Image Processing Te...

引用

Signal processing and Intelligent Computing (SPIC), International conference on

作者： Bingcan Yang Xiai Chen School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

image processing is a technique that involves the manipulation and enhancement of digital images. It encompasses various aspects such as image acquisition, image preprocessing, image enhancement, image segmentation, feature extraction, and object detection. The purpose of image processing is to process and enhance images using computer technology, aiming to achieve higher image quality for subsequent processing and applications. In practical applications, image processing techniques employ different algorithms and methods to achieve various processing and enhancement effects. Additionally, image processing techniques can be applied in fields such as medicine, security, autonomous driving, VR/AR, etc. For instance, in the medical field, image processing techniques can be utilized for image segmentation and diagnosis of medical images, thereby improving the accuracy and analytical capabilities of medical imaging. In the security field, image processing techniques can be employed for tasks such as video surveillance and facial recognition, enhancing the efficiency and accuracy of security monitoring. In the domain of autonomous driving, image processing techniques can be used for detecting and recognizing the surrounding environment of vehicles, thereby enhancing the safety and performance of autonomous driving systems. In conclusion, image processing technology is a very important technology. By continuously improving the accuracy and reliability of the algorithm, it is expected to be applied in a wider range of applications.

关键词： image segmentation image recognition Accuracy image processing Face recognition Signal processing algorithms Signal processing Video surveillance Medical diagnostic imaging Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Direction-of-arrival estimation with new versions of Min-Norm algorithm based on Nyström method 7

Direction-of-arrival estimation with new versions of Min-Nor...

引用

7th International conference on image and Signal processing and their Applications, ISPA 2022

作者： Naceur, Aounallah Ali, Khalfa Kasdi Merbah University Faculty of New Information Technologies and Communication Department of Electronic and Telecommunications Ouargla30000 Algeria Mohamed Boudiaf University Faculty of Technologies Department of Electronic M'Sila28000 Algeria

ISBN: (纸本)9781665480420

Direction-of-arrival estimation is a significant problem in many telecommunication systems which their architecture is composed with antenna arrays. In literature, several algorithms were proposed as a challenge, for different scenarios, to detect rapidly and accurately the direction of impinging signals on the antenna array. In this paper firstly, we use the Nyström method to develop a low computational Min-Norm version for solving the problem of direction-of-arrival estimation by spectral peak searching. Then, we generalize the root version of the proposed algorithm. Finally, we give some simulation results for demonstrating the efficiency and the performances of the new proposed algorithm versions. © 2022 IEEE.

关键词： Array processing

来源：评论

学校读者我要写书评

暂无评论

Comparison and Application of Vehicle Target Detection Methods Based on YOLOv5s and YOLOv7 7

Comparison and Application of Vehicle Target Detection Metho...

引用

7th IEEE International conference on Information systems and Computer Aided Education, ICISCAE 2024

作者： Gu, Chenyu Du, Hong Zhang, Xiaozheng Li, Lidan Yang, Zhonglin Liu, Gaotian China Northern Vehicle Research Institute Beijing China

ISBN: (纸本)9798350350760

Currently, the methods for pedestrian detection have undergone significant expansion, yet vehicle target detection still retains immense potential for widespread application in the field of intelligent recognition. Nevertheless, vehicle target detection encounters challenges in terms of detection effectiveness, impacted by factors such as lighting conditions, environmental variations, and occlusions. This study centers on vehicle target detection, aiming to tackle the issues of difficult detection, easy missed detection, and algorithm selection within complex backgrounds. By utilizing the YOLOv5s and YOLOv7 algorithms, we have constructed a dataset that encompasses images featuring vehicles against complex backgrounds and in small scales. This dataset is then used to train the models, which are subsequently employed to perform target recognition for vehicles individually. Through comparative experimentation, we have proven the superiority of the YOLOv7 algorithm in detecting vehicles amidst complex backgrounds and those of small scales. ©2024 IEEE.

关键词： image processing vehicle target detection YOLOv5s YOLOv7

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 << < 78 79 80 81 82 83 84 85 86 87 > >>

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：