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

12,548 篇 会议
192 篇 期刊文献
161 册 图书

馆藏范围

12,901 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

6,491 篇 工学
- 4,273 篇 计算机科学与技术...
- 2,180 篇 软件工程
- 1,872 篇 电气工程
- 1,277 篇 信息与通信工程
- 825 篇 控制科学与工程
- 652 篇 光学工程
- 462 篇 生物医学工程（可授...
- 440 篇 电子科学与技术（可...
- 435 篇 机械工程
- 425 篇 仪器科学与技术
- 316 篇 生物工程
- 220 篇 测绘科学与技术
- 152 篇 材料科学与工程（可...
- 142 篇 航空宇航科学与技...
- 133 篇 交通运输工程
- 99 篇 安全科学与工程
- 86 篇 网络空间安全
3,125 篇 理学
- 2,083 篇 物理学
- 888 篇 数学
- 359 篇 生物学
- 246 篇 系统科学
- 224 篇 统计学（可授理学、...
- 109 篇 化学
1,429 篇 医学
- 1,268 篇 临床医学
- 192 篇 特种医学
- 158 篇 基础医学(可授医学...
- 99 篇 药学(可授医学、理...
691 篇 管理学
- 422 篇 管理科学与工程(可...
- 291 篇 图书情报与档案管...
- 84 篇 工商管理
58 篇 法学
57 篇 农学
29 篇 教育学
27 篇 文学
25 篇 经济学
17 篇 军事学
16 篇 艺术学
1 篇 哲学

主题

2,645 篇 image processing
1,386 篇 image segmentati...
1,143 篇 signal processin...
609 篇 cameras
594 篇 feature extracti...
584 篇 image edge detec...
521 篇 signal processin...
472 篇 image reconstruc...
461 篇 real-time system...
460 篇 image coding
390 篇 algorithm design...
334 篇 image color anal...
308 篇 deep learning
306 篇 image enhancemen...
306 篇 pixel
300 篇 real time system...
293 篇 object detection
290 篇 computer archite...
283 篇 neural networks
282 篇 hardware

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

12,604 篇 英文
211 篇 其他
74 篇 中文
20 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 12901 条记录，以下是401-410 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：

Secure Vision: Enhancing Data Security in Wireless Sensor Networks through image processing 8

Secure Vision: Enhancing Data Security in Wireless Sensor Ne...

引用

8th International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Swamy, B. Venkata Gopi, S. Sudhakar, Kattupalli Girish, Pechetti Rani, M. Janaki Upadhyay, Shrikant B V Raju Institute of Technology Department of Chemistry Telangana State India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Cse Chennai Avadi India Lakireddy Bali Reddy College of Engineering Department of Ai & Ds Mylavaram India Bonam Venkata Chalamayya Institute of Technology and Science Batlapalem Amalapuram India Dr. Mgr Educational and Research Institute Department of Ece Chennai India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798350376425

The secure Wireless Sensor Network (WSN) architecture was designed in such a way that the tradeoffs among efficiency, scalability and security were balanced. It was consisted of several sensor nodes, cluster heads, base station as well as the control center all of them played a vital role in functioning and managing of data. This network security was provided with a layered security approach like the physical, data link, network, transport, and application layers. Data security and integrity are secured through advanced image processing algorithms, and reliable communication protocol. Regular maintenance, constant monitoring and hardening solutions through resilience and fault tolerance mechanisms added a layer of trust in securing this WSN. A comparative analysis was made using different algorithms, such as Intrusion Detection systems (IDS) and detection accuracy is 98% and proposed model which has shown a better result in the energy consumption, data transmission latency, encryption time, detection precision as well as efficiency to insure an original data integrity. © 2024 IEEE.

关键词： Data integrity

来源：评论

学校读者我要写书评

暂无评论

Chinese image Description Generation Model Based on Recurrent Fusion Encoding 5th

Chinese Image Description Generation Model Based on Recurren...

引用

5th International conference on 3D Imaging Technologies-Multidimensional Signal processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Zhou, Shiyu Donghua University Shanghai China

ISBN: (纸本)9789819751839

The image description job is a crucial area of research in the nexus of computer vision and applications for natural language processing. The objective is to produce accurate text descriptions using the picture attributes retrieved by the model. The conventional encoder-decoder model produces an inadequate encoding feature because it does less direct dimensionality reduction on images and is deficient in sequence feature information. This research suggests a recurrent fusion encoding-based Chinese picture description generation model to solve the aforementioned issues. R-CNN is used to extract the image's features first. Then, at the encoding side, gated recurrent units and a soft attention mechanism are used to build a recurrent fusion network for full sequence fusion of the image features. Finally, the sequence feature information is combined with a self-attention mechanism for multi-level interaction before being sent to the encoding side. I carried out enough tests on the Flickr_8k dataset and the Ai_Challenger dataset to confirm the model’s validity. According to the experimental data, the model performs better than some Chinese image description algorithms in each index by 0.2–4.2% points, and the generated statements are more accurate and sufficient for image description. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

EgpuIP: An Embedded GPU Accelerated Library for image processing 24

EgpuIP: An Embedded GPU Accelerated Library for Image Proces...

引用

24th IEEE International conference on High Performance Computing and Communications, 8th IEEE International conference on Data Science and systems, 20th IEEE International conference on Smart City and 8th IEEE International conference on Dependability in Sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Wang, Luhan Jia, Haipeng Zhang, Yunquan Li, Kun Wei, Cunyang Institute of Computing Technology Chinese Academy of Sciences State Key Lab of Processors Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Microsoft Research China

ISBN: (纸本)9798350319934

With the advances of embedded GPUs' programming models like GLES and OpenCL, the mobile processor has gained more parallel computing capability, which enables real-time image processing on portable devices. GLES is an excellent option to implement high-performance image processing on embedded GPUs due to its low hardware overhead. However, most GLES studies only focus on porting specific algorithms to embedded GPUs without a general optimization guide. In order to address the pending problems, this paper presents effective performance optimization chains to guide the optimization of image processing algorithms by using GLES. The image processing algorithms can be divided into three modes including data-independent, data-sharing and data-related according to their memory access and calculation characteristics. Based on this classification, our optimization chains contain four optimization directions. 1) Optimizing access to off-chip memory for the memory-bound data-independent algorithm;2) Exploiting data locality by utilizing shared memory and cache for the data-sharing algorithm;3) Redesigning the algorithm to optimize the sharing of computational results between threads for the data-related algorithm;4) Making full use of computation resource for the above three algorithms. Based on these optimization chains, we design an embedded GPU accelerated image processing library, EgpuIP. To evaluate specific optimization methods and performance improvements, we employ histogram equalization, Gaussian pyramid and integral filter as the representative algorithm from EgpuIP and adequately optimize them guided by the proposed optimization chains. Compared to the OpenCV, experiments show that the three algorithms in EgpuIP provide up to 19×88×, and 3× speedup respectively. © 2022 IEEE.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Braille-to-Voice Converter Using image processing 2nd

Braille-to-Voice Converter Using Image Processing

引用

2nd International conference on Advances in Computational Intelligence and Informatics, ICACII 2023

作者： Prasad, P. Rajendra Ahmed, Roshan Zameer Lingamurthy, Chethan Raju Chaitra, A.M. Deepak, H.R. Ramaiah Institute of Technology Bangalore560054 India Presidency University Bangalore India

ISBN: (纸本)9789819747269

Approximately 2.2 billion people in the world are visually impaired and rely on assistance to meet their basic needs. Education is a fundamental human need and plays a crucial role in empowering individuals. For visually impaired individuals, education can not only integrate them into society but also enhance their professional and academic abilities. To facilitate better education for the visually impaired, specialized books, educational materials, and devices are necessary. Braille is a tactile system designed for people who are blind, enabling them to read and write through touch. Proposed work aims to improve the education of visually impaired individuals by developing a braille-to-voice converter. The system will use image processing techniques to capture an image of braille text, which will then be analyzed using computer vision algorithms to extract the text and convert it to speech. The ultimate goal is to create a cost-effective, accurate, and user-friendly tool that can be easily integrated into the daily lives of visually impaired individuals. With this system, visually impaired individuals will be able to easily and quickly convert braille text to speech in real time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Intelligent Frame and Table Segmentation in Blueprint Documents: Method and Implementation 6th

Intelligent Frame and Table Segmentation in Blueprint Docume...

引用

6th conference on Computational Methods in systems and Software (CoMeSySo)

作者： Hasan, Fudail Kashevnik, Alexey ITMO Univ St Petersburg Russia SPC RAS St Petersburg Russia Petrozavodsk State Univ PetrSU Petrozavodsk Russia

ISBN: (纸本)9783031214370;9783031214387

Blueprints are documents that contain the drawing of a design and the information that explains this design. Recently, the task to automatically recognize the information in the blueprint documents has become required. Segmenting the frame and tables in the blueprint is the first step of understanding the blueprint document. In this paper, we explain an automated method for frame and table segmentation. The proposed method processes the blueprint as an image and defines all the parts (pixels) of the blueprint that belongs to the frame or tables. It finds all the lines in the blueprint's image and decide which combinations of lines construct frame and tables. It can process blueprints that have high resolution. The proposed method allows to isolate frame and tables in the blueprint document. We achieved an accuracy of 99% for excellent quality documents.

关键词： Frame and table segmentation Blueprint processing Table detection Lines segmentation

来源：评论

学校读者我要写书评

暂无评论

The Impact of Preprocessing on Face Recognition using Pseudorandom Pixel Placement 29

The Impact of Preprocessing on Face Recognition using Pseudo...

引用

29th International conference on systems, Signals and image processing (IWSSIP)

作者： Hadis, Muhammad Sabirin Akita, Junichi Toda, Masashi Nurzaenab Kanazawa Univ Dept Elect Engn & Comp Sci Kanazawa Japan Kumamoto Univ Ctr Management Informat Technol Kumamoto Japan STMIK AKBA Study Program Informat Engn Makassar Indonesia

ISBN: (数字)9781665495783

ISBN: (纸本)9781665495783

The condition of face images, data processing algorithms, and hardware capabilities can influence the accuracy of face recognition. Several studies have been conducted to increase performance of face recognition. One of the steps is to create or even improve the methods in preprocessing as one of the essential steps that can affect accuracy. This paper proposed a pseudorandom pixel placement method applied to the preprocessing step in face recognition to know the impact on accuracy. Eight face objects were used in this study. One face image for one object as training data was taken via a single-lens digital reflex camera and a smartphone. One video for one object was taken from Closed Circuit Television with two different placement angle conditions for testing data. The experiment was carried out with four variations of the basic resolution size of the face image in the testing data to see the performance of the proposed method. The result is five of eight face objects have improved accuracy than without using pseudorandom pixel placement. The best average accuracy result using the proposed method is 63.76% higher than without using the proposed method with a value of 60.09%, so preprocessing using the pseudorandom pixel placement on face recognition can increase accuracy.

关键词： Face Recognition Pseudorandom Pixel Placement One image Training Data image processing Computer Vision

来源：评论

学校读者我要写书评

暂无评论

Post-processing of Thresholding or Deep Learning Methods for Enhanced Tissue Segmentation of Whole-Slide Histopathological images

Post-Processing of Thresholding or Deep Learning Methods for...

引用

18th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2025

作者： Marczyk, Michal Wrobel, Agata Merta, Julia Polanska, Joanna Department of Data Science and Engineering Silesian University of Technology Gliwice44-100 Poland Yale Cancer Center Yale School of Medicine New HavenCT06511 United States Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Digital pathology allows for the efficient storage and advanced computational analysis of stained histopathological slides of various tissues. Tissue segmentation is a crucial first step of digital pathology aimed at eliminating background, pen markings, and other artifacts, reducing image size, and increasing the efficiency of further analysis. In most cases, color thresholding or deep learning models are used, but their effectiveness is reduced due to complex artifacts and huge color variations between slides. We propose a post processing method to increase the tissue segmentation performance of any initial segmentation algorithm. Using a set of 197 manually annotated histopathological images of breast cancer patients and 63 images of endometrial cancer patients, we tested our method with 3 thresholding techniques and 3 deep learning-based algorithms by calculating the Dice index, Jaccard index, precision, and recall. In both datasets, applying post processing increased precision and recall for thresholding methods and mostly precision for deep learning models. Overall, applying post-processing gave better tissue segmentation performance than initial segmentation methods, significantly increasing Dice and Jaccard indices. Our results proved that thanks to post-processing, the tissue segmentation pipeline is more robust to noises and artifacts commonly present in histopathological images. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Advanced HLS for Reconfigurable image processing in Big Data systems 12th

Advanced HLS for Reconfigurable Image Processing in Big Da...

引用

12th International conference on Big Data and Artificial Intelligence, BDA 2024

作者： Bhagirath, K. Pant, Dheeraj Tiwari, Abhishek Khaneja, Vivek Noida201309 India

ISBN: (纸本)9783031818202

This paper introduces novel HLS techniques for reconfigurable and memory-efficient image processing within deep learning frameworks, addressing inherent limitations of current deep learning accelerators (DLAs) due to their dependency on the host processor, leading to pipeline delays and reduced throughput. The proposed approach emphasizes parallelization, on-chip buffering, and scalability, enhancing computational efficiency and throughput for AI applications in big data and edge computing environments. Methodologically, the paper emphasizes mathematical analysis, hardware architecture specification, HLS modeling, Verilog RTL implementation. By addressing these challenges, this work contributes to advancing the performance capabilities of DLAs in deep learning inference tasks. The algorithms integrates seamlessly with DLA IP subsystems, such as AXI interfaces, external (DRAM) and internal (SRAM) memory interfaces, and activation/pooling engines. Key contributions include advanced algorithm design to enhance memory efficiency and reconfigurability, essential for adapting to diverse hardware architectures. Experimental validation demonstrates substantial improvements in computational speed and resource utilization compared to traditional methods, making it suitable for intensive AI tasks in big data analytics. In conclusion, this research presents a framework for integrating HLS techniques into hardware accelerators, facilitating efficient image processing across diverse applications in big data and edge computing. These advancements aim to bolster DLAs’ capabilities in handling complex AI workloads effectively, promising enhanced solutions for AI-driven domains. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

RestoreAgent: Autonomous image Restoration Agent via Multimodal Large Language Models 38

RestoreAgent: Autonomous Image Restoration Agent via Multimo...

引用

38th conference on Neural Information processing systems, NeurIPS 2024

作者： Chen, Haoyu Li, Wenbo Gu, Jinjin Ren, Jingjing Chen, Sixiang Ye, Tian Pei, Renjing Zhou, Kaiwen Song, Fenglong Zhu, Lei The Hong Kong University of Science and Technology Guangzhou China Huawei Noah's Ark Lab Canada The University of Sydney Australia The Hong Kong University of Science and Technology Hong Kong

Natural images captured by mobile devices often suffer from multiple types of degradation, such as noise, blur, and low light. Traditional image restoration methods require manual selection of specific tasks, algorithms, and execution sequences, which is time-consuming and may yield suboptimal results. All-in-one models, though capable of handling multiple tasks, typically support only a limited range and often produce overly smooth, low-fidelity outcomes due to their broad data distribution fitting. To address these challenges, we first define a new pipeline for restoring images with multiple degradations, and then introduce RestoreAgent, an intelligent image restoration system leveraging multimodal large language models. RestoreAgent autonomously assesses the type and extent of degradation in input images and performs restoration through (1) determining the appropriate restoration tasks, (2) optimizing the task sequence, (3) selecting the most suitable models, and (4) executing the restoration. Experimental results demonstrate the superior performance of RestoreAgent in handling complex degradation, surpassing human experts. Furthermore, the system's modular design facilitates the fast integration of new tasks and models. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fingerprint image Enhancement Method Based on U-Net Model 1st

Fingerprint Image Enhancement Method Based on U-Net Model

引用

1st International conference on AI-generated Content, AIGC 2023

作者： Cheng, Yu-Hsin Su, Sheng-Gui Lin, Yih-Lon Hsu, Hsiang-Chen National Yunlin University of Science and Technology Yunlin Taiwan I-Shou University Kaohsiung Taiwan

ISBN: (纸本)9789819975860

Fingerprint image enhancement is a vital image processing technology that finds applications in fingerprint identification, matching, and biometric authentication. Its objective is to improve the performance and accuracy of fingerprint identification systems by enhancing the quality, clarity, and contrast of fingerprint images while reducing noise. Traditional algorithms often require adjusting parameters based on individual fingerprint images, resulting in inconsistent enhancement results. To address this challenge, this paper proposes a deep learning-based approach for fingerprint image enhancement. Experimental results demonstrate the effectiveness of U-Net architecture with different depths and the impact of incorporating attention gate. Actually, a U-Net model with a depth of six achieves superior performance, surpassing other depths, and the inclusion of attention gate further enhances the results. The proposed method not only retains more fingerprint features but also produces smoother structures and reduces noise surrounding the fingerprint image. These findings contribute to advancing fingerprint image enhancement techniques, bolstering the accuracy and performance of fingerprint identification systems in applications such as forensic analysis and biometric authentication. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image enhancement

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 << < 37 38 39 40 41 42 43 44 45 46 > >>

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：