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

2,747 篇 会议
163 篇 期刊文献
19 册 图书

馆藏范围

2,929 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,738 篇 工学
- 1,170 篇 计算机科学与技术...
- 745 篇 电气工程
- 441 篇 软件工程
- 340 篇 信息与通信工程
- 232 篇 控制科学与工程
- 221 篇 生物医学工程（可授...
- 128 篇 光学工程
- 109 篇 仪器科学与技术
- 103 篇 电子科学与技术（可...
- 76 篇 机械工程
- 60 篇 生物工程
- 33 篇 测绘科学与技术
- 27 篇 材料科学与工程（可...
- 24 篇 交通运输工程
- 22 篇 化学工程与技术
- 18 篇 安全科学与工程
- 14 篇 动力工程及工程热...
469 篇 理学
- 216 篇 数学
- 181 篇 物理学
- 85 篇 生物学
- 59 篇 统计学（可授理学、...
- 53 篇 系统科学
- 27 篇 地球物理学
- 19 篇 化学
400 篇 医学
- 267 篇 临床医学
- 124 篇 特种医学
- 45 篇 基础医学(可授医学...
- 25 篇 药学(可授医学、理...
187 篇 管理学
- 146 篇 管理科学与工程(可...
- 48 篇 图书情报与档案管...
14 篇 法学
13 篇 军事学
11 篇 农学
10 篇 艺术学
4 篇 经济学
2 篇 教育学

主题

301 篇 computational mo...
260 篇 image processing
246 篇 signal processin...
225 篇 image segmentati...
208 篇 signal processin...
195 篇 feature extracti...
175 篇 image reconstruc...
136 篇 computational in...
128 篇 image coding
123 篇 deep learning
114 篇 artificial intel...
113 篇 training
85 篇 computational ef...
84 篇 image edge detec...
83 篇 computational co...
82 篇 visualization
81 篇 neural networks
81 篇 computer vision
78 篇 accuracy
75 篇 image analysis

机构

14 篇 signal and image...
11 篇 obuda univ john ...
7 篇 john von neumann...
6 篇 department of co...
5 篇 shanghai jiao to...
5 篇 nanyang technol ...
5 篇 univ chinese aca...
4 篇 centre for multi...
4 篇 univ chinese aca...
4 篇 xidian univ sch ...
4 篇 xidian univ natl...
4 篇 tsinghua univ de...
4 篇 huazhong univ sc...
4 篇 obuda university...
4 篇 wuhan univ techn...
4 篇 keio univ dept e...
4 篇 obuda univ docto...
4 篇 univ memphis dep...
4 篇 department of el...
3 篇 department of el...

作者

9 篇 chen yen-wei
6 篇 gabbouj moncef
6 篇 mendel jerry m.
6 篇 kozlovszky miklo...
6 篇 tefas anastasios
6 篇 egiazarian karen
6 篇 richard m. leahy
5 篇 pitas ioannis
5 篇 hamid r. tizhoos...
5 篇 fang liu
5 篇 zhaokui li
4 篇 xiangbin shi
4 篇 molnar bela
4 篇 r.m. leahy
4 篇 li xin
4 篇 tao yang
4 篇 yuan xin
4 篇 jerry m. mendel
4 篇 miklos kozlovszk...
4 篇 loncaric sven

语言

2,908 篇 英文
12 篇 其他
9 篇 中文

检索条件"任意字段=IEEE Symposium on Computational Intelligence in Image and Signal Processing"

共 2929 条记录，以下是2851-2860 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：

QUANTOF: multi-GPU-based list-mode fully quantitative TOF PET image reconstruction

QUANTOF: multi-GPU-based list-mode fully quantitative TOF PE...

引用

ieee symposium on Nuclear Science (NSS/MIC)

作者： Z. Yuan F. Zhan H. Lu C. Li Y. Hou H. Wang J. Hua R. Liao J. Jiang Key Laboratory of Beam Technology of Ministry of Education College of Nuclear Science and Technology Beijing Normal University Beijing China Department of Nuclear Medicine The First Affiliated Hospital of USTC Division of Life Sciences and Medicine University of Science and Technology of China Anhui China School of Artificial Intelligence Beijing Normal University Beijing China

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

Positron Emission Tomography (PET) plays a pivotal role in the early detection and precise diagnosis of various diseases, including cancer, neurological disorders, and heart conditions. Ordered subset expectation maximization (OSEM) algorithm is the most commonly used image reconstruction algorithm. To address the high computational costs associated with this algorithm, numerous studies have explored the effectiveness of GPU acceleration. However, these studies have predominantly focused on the forward and backward projection components of iterative algorithms, neglecting correction techniques which are essential for PET image reconstruction, such as scatter correction. This work introduces a multi-GPU-based list-mode fully quantitative Time-of-Flight (TOF) PET image reconstruction technique, named QUANTOF, that integrates all corrections during PET image iterative reconstruction on GPUs. Additionally, optimizations have been applied to the backprojection algorithm, resulting in a two-fold increase in speed compared to the pre-optimized version. Validation using experimental datasets from a Siemens Biograph Vision PET/CT scanner demonstrates that this technique significantly reduces reconstruction time costs while achieving exceptional quantitative accuracy.

关键词： Neurological diseases Heart Microwave integrated circuits Semiconductor detectors Graphics processing units Iterative methods Positron emission tomography

来源：评论

学校读者我要写书评

暂无评论

image Semantic Segmentation Based on the GAN Auxiliary Network

Image Semantic Segmentation Based on the GAN Auxiliary Netwo...

引用

symposium of image, signal processing, and Artificial Vision (STSIVA)

作者： Jinshuo Zhang Zhicheng Wang Songyan Zhang Gang Wei Zhiqiang Xiong Meng Yang CAD Research Center Tongji University Shanghai China China Ship Development and Design Center Wuhan China

ISBN: (纸本)9781665426565

To enhance the performance of existing deep neural networks in semantic segmentation while preserving efficiency at the same time, a semantic segmentation network with the help of GAN (Generative Adversarial Networks) is proposed. The method consists of a generator and a discriminator. The segmentation results obtained from the generator are encoded and then fed into the discriminator to obtain the pixel-wise uncertainty values. Such uncertainty values are taken as weights for the calculation of CEGU (Cross-Entropy with GAN Uncertainty) to help the optimization of the generator. The discriminator is removed after training. Experiment results show that the mean IoU (Intersection over Union) scores of the segmentation results grow by 4.7% and 3.2% respectively on ResNet-50 and ResNet18, after using the GAN auxiliary method along with the CEGU. It shows that such a GAN auxiliary network can significantly improve the performance of basic end-to-end methods with various backbones on the semantic segmentation task, without introducing extra computation cost in the test phase.

关键词： Training image segmentation Uncertainty Costs computational modeling Semantics Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Hidden Challenge in Deep-Learning Real-Time Object Detection on Edge Devices

Hidden Challenge in Deep-Learning Real-Time Object Detection...

引用

Midwest symposium on Circuits and Systems (MWSCAS)

作者： Marcus F. Nicolas Dalila B. Megherbi Department of Electrical and Computer Engineering UMASS Lowell CMINDS Research Center Lowell USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

As the need arises for edge intelligence, which combines edge-computing with artificial intelligence, efficient and accurate algorithms are increasingly needed. Edge computing allows AI applications to be executed in real-time, closest to hardware devices/systems, thus reducing latency that could be introduced if traversing the cloud or sent to some storage unit. The aim is the needed real-time information processing, among other benefits. Notwithstanding the advantages of Edge-AI, a challenge that is not generally addressed in many such real-time detection and recognition DL models is the effect of an object rotation on real-time object detection accuracy. In particular, object label uncertainty can be introduced in rotated object detection because the detected shape is not foreseen. The focus of this paper is to highlight how real-time object detection can be affected by rotation, a problem of importance in the field. We selected a particular architecture, Efficientdet, and implemented it on a Raspberry Pi 4 to study this rotational object detection handicap. This paper also aims to increase awareness and tender possible solutions in hopes that future researchers and engineers can design DL models on edge computing devices that will significantly diminish the impacts of an object rotation on its real-time object detection accuracy.

关键词： Accuracy Uncertainty image edge detection computational modeling Object detection Real-time systems Hardware

来源：评论

学校读者我要写书评

暂无评论

Single Dendritic Neural Classification with Functional Weight-enhanced Differential Evolution

Single Dendritic Neural Classification with Functional Weigh...

引用

symposium of image, signal processing, and Artificial Vision (STSIVA)

作者： Ziqian Wang Kaiyu Wang Jiaru Yang Zheng Tang Faculty of Engineering University of Toyama Toyama Japan

ISBN: (纸本)9781665426565

As current mainstream deep learning models based on neural networks have been long criticized because of their complex structures, attempts in formulating a single neural model have raised much attention. Owing to the nonlinear information processing ability, dendritic neuron model (DNM) has shown its great potential in classification problems over the past decades. However, designing an effective learning algorithm for training DNM is still an open question due to the issues of local optima trapping and overfiting caused by traditional back-propagation (BP) algorithm. In this study, a novel functional weight-enhanced differential evolutionary algorithm (termed FWDE) is proposed to solve the aforementioned problems. By introducing Gaussian distribution function into weight generation of fitness-distance balance selection strategy, FWDE obtains significantly better classification accuracy with faster convergence speed compared with other representative non-BP and BP algorithms. The experimental results verify the great performance of FWDE, indicating that DNM with an powerful learning algorithm is considerably more effective.

关键词： Deep learning Training Proteins computational modeling Neurons Text categorization Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

DMTCP: Transparent checkpointing for cluster computations and the desktop

DMTCP: Transparent checkpointing for cluster computations an...

引用

International symposium on Parallel and Distributed processing (IPDPS)

作者： Jason Ansel Kapil Arya Gene Cooperman Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA College of Computer and Information Science Northeastern University Boston MA USA

DMTCP (distributed multithreaded checkpointing) is a transparent user-level checkpointing package for distributed applications. Checkpointing and restart is demonstrated for a wide range of over 20 well known applications, including MATLAB, Python, TightVNC, MPICH2, OpenMPI, and runCMS. RunCMS runs as a 680 MB image in memory that includes 540 dynamic libraries, and is used for the CMS experiment of the Large Hadron Collider at CERN. DMTCP transparently checkpoints general cluster computations consisting of many nodes, processes, and threads; as well as typical desktop applications. On 128 distributed cores (32 nodes), checkpoint and restart times are typically 2 seconds, with negligible run-time overhead. Typical checkpoint times are reduced to 0.2 seconds when using forked checkpointing. Experimental results show that checkpoint time remains nearly constant as the number of nodes increases on a medium-size cluster. DMTCP automatically accounts for fork, exec, ssh, mutexes/ semaphores, TCP/IP sockets, UNIX domain sockets, pipes, ptys (pseudo-terminals), terminal modes, ownership of controlling terminals, signal handlers, open file descriptors, shared open file descriptors, I/O (including the readline library), shared memory (via mmap), parent-child process relationships, pid virtualization, and other operating system artifacts. By emphasizing an unprivileged, user-space approach, compatibility is maintained across Linux kernels from 2.6.9 through the current 2.6.28. Since DMTCP is unprivileged and does not require special kernel modules or kernel patches, DMTCP can be incorporated and distributed as a checkpoint-restart module within some larger package.

关键词： Checkpointing Kernel Packaging Libraries Sockets MATLAB Collision mitigation Large Hadron Collider Yarn Runtime

来源：评论

学校读者我要写书评

暂无评论

Auto-Tuning Dedispersion for Many-Core Accelerators

Auto-Tuning Dedispersion for Many-Core Accelerators

引用

International symposium on Parallel and Distributed processing (IPDPS)

作者： Alessio Sclocco Henri E. Bal Jason Hessels Joeri van Leeuwen Rob V. van Nieuwpoort Faculty of Sciences Vrije Universiteit Amsterdam Amsterdam Netherlands ASTRON Netherlands Institute for Radio Astronomy Dwingeloo Netherlands

ISBN: (纸本)9781479938018

Dedispersion is a basic algorithm to reconstruct impulsive astrophysical signals. It is used in high sampling-rate radio astronomy to counteract temporal smearing by intervening interstellar medium. To counteract this smearing, the received signal train must be dedispersed for thousands of trial distances, after which the transformed signals are further analyzed. This process is expensive on both computing and data handling. This challenge is exacerbated in future, and even some current, radio telescopes which routinely produce hundreds of such data streams in parallel. There, the compute requirements for dedispersion are high (petascale), while the data intensity is extreme. Yet, the dedispersion algorithm remains a basic component of every radio telescope, and a fundamental step in searching the sky for radio pulsars and other transient astrophysical objects. In this paper, we study the parallelization of the dedispersion algorithm on many-core accelerators, including GPUs from AMD and NVIDIA, and the Intel Xeon Phi. An important contribution is the computational analysis of the algorithm, from which we conclude that dedispersion is inherently memory-bound in any realistic scenario, in contrast to earlier reports. We also provide empirical proof that, even in unrealistic scenarios, hardware limitations keep the arithmetic intensity low, thus limiting performance. We exploit auto-tuning to adapt the algorithm, not only to different accelerators, but also to different observations, and even telescopes. Our experiments show how the algorithm is tuned automatically for different scenarios and how it exploits and highlights the underlying specificities of the hardware: in some observations, the tuner automatically optimizes device occupancy, while in others it optimizes memory bandwidth. We quantitatively analyze the problem space, and by comparing the results of optimal auto-tuned versions against the best performing fixed codes, we show the impact that auto-tuning ha

关键词： Artificial intelligence Delays Radio astronomy Equations Algorithm design and analysis Dispersion Extraterrestrial measurements

来源：评论

学校读者我要写书评

暂无评论

Quantum Annealing based SVM Outperforms Classical SVM in Cloud Feature Remote Sensing image Classification

Quantum Annealing based SVM Outperforms Classical SVM in Clo...

引用

Remote Sensing symposium (InGARSS), 2020 ieee India Geoscience and

作者： Indranil Misra S. Manthira Moorthi Debajyoti Dhar Signal and Image Processing Area Space Applications Centre Indian Space Research Organisation (ISRO) Ahmedabad India

ISBN: (数字)9798350390346

ISBN: (纸本)9798350390353

The increasing complexity and volume of remote sensing data necessitate advanced computational techniques for efficient and accurate image classification. This study explores the efficacy of Quantum Annealing based Support Vector Machines (QASVM) in comparison to classical Support Vector Machines (SVM) for classifying cloud features in remote sensing images. Quantum annealing, leveraging principles of quantum mechanics, promises to solve optimization problems more efficiently and accurately than classical methods, particularly in high-dimensional data spaces typical of remote sensing applications. Our experimental framework involved the classification of cloud features using a comprehensive dataset of Indian Nano Satellite (INS-2B) Nano-MX satellite imagery. The QA-SVM is implemented on a D-Wave quantum annealer based on the Adiabatic Quantum Computation (AQC) model, while the classical SVM utilizes a traditional computing setup. Performance metrics, including overall accuracy and F1 score, are evaluated. The results demonstrated that QA-SVM achieved higher overall accuracy and F1 score compared to its classical counterpart on the Nano-MX test image. It is found that the overall accuracy of QA-SVM is increased by 6.7% while the F1 score is increased by 4.5% with respect to classical SVM. This performance gain is attributed to the quantum annealer’s ability to explore a vast solution space more effectively, avoiding local minima that often hinder classical SVMs.

关键词： Support vector machines Annealing Accuracy Satellites Quantum mechanics Performance gain Quantum annealing Satellite images Remote sensing image classification

来源：评论

学校读者我要写书评

暂无评论

Efficient Vision Transformer Deployment on Google Coral Through Knowledge Distillation

Efficient Vision Transformer Deployment on Google Coral Thro...

引用

East-West Design & Test symposium (EWDTS)

作者： Vazgen Melikyan Tigran Khachatryan Davit Galstyan Eduard Harutyunyan National Polytechnic University of Armenia Synopsys Armenia CJSC Yerevan Armenia Synopsys Armenia Educational Department National Polytechnic University of Armenia Yerevan Armenia

ISBN: (数字)9798331515768

ISBN: (纸本)9798331515775

With the development of AI, the models are becoming more complex and resource intensive. There is a need to create smaller but at the same time satisfactory performance models that will run on resource-constrained devices. This paper explores enhancing the efficiency of the MobileNetV2 architecture using the power of the Vision Transformer through knowledge distillation. The goal was to leverage the complex insights of the Vision Transformer to improve the capabilities of MobileNetV2. As a result, the refined model outperformed its original version by about 5% (from 81.7% to 86.5%). The model was then placed on the Coral Dev Board edge device and due to the weight adjustments, there was a slight decrease in accuracy to 84.3%. Despite this, it reduced its processing latency by more than half, from 0.0076 seconds to 0.0037 seconds, proving a valuable approach for efficient and real-time edge computing applications.

关键词： Performance evaluation Computer vision Accuracy Quantization (signal) computational modeling Transformers Real-time systems Internet Artificial intelligence Edge computing

来源：评论

学校读者我要写书评

暂无评论

Ultrasonic Imaging and Flaw Detection with Optimized Convolutional Transformer Neural Networks

Ultrasonic Imaging and Flaw Detection with Optimized Convolu...

引用

ieee symposium (IUS) Ultrasonics

作者： Xin Zhang Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago Illinois U.S.A.

Flaw detection using the ultrasonic imaging technique has been widely used for Structural Health Monitoring (SHM). Ultrasonic testing has the advantages of one-sided measurement, high penetration depth, and inspection accuracy. Artificial intelligence (AI) such as Deep Learning (DL) methods can automate the inspection process with high reliability for imaging and SHM. Neural Networks (NNs) and DL methods can detect flaws using ultrasonic images with high accuracy but suffer extensive computational costs for training and deployment. In this study, we propose a lightweight transformer NN, UFDCTNet: Ultrasonic Flaw Detection Convolutional Transformer Neural Network (TNN), optimized with data-efficient Convolutional NN (CNN) for flaw detection using ultrasonic imaging. TNN utilizes the self-attention network architecture that learns global representations and allows high parallelism in computation resulting in reduced training time. CNNs learn local representations with fewer parameters because of inherent spatial inductive bias. This UFDCTNet utilizes the advantages of CNNs to learn spatially local representations resulting in fewer model parameters for fast training. For performance analysis, we trained data-efficient TNN and CNN using ultrasonic images to detect flaws. To examine training results, NNs are trained with the USimgAIST dataset consisting of 7000 experimental B-scan images representing without-flaw and with-flaw cases. A pulsed laser ultrasonic scanning system was used to collect these B-scan images from 17 stainless steel specimen plates with various types of flaws and some plates without any damage.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Benchmarking End-to-End Behavioural Cloning on Video Games

Benchmarking End-to-End Behavioural Cloning on Video Games

引用

ieee symposium on computational intelligence and Games, CIG

作者： Anssi Kanervisto Joonas Pussinen Ville Hautamäki School of Computing University of Eastern Finland Joensuu Finland

ISBN: (数字)9781728145334

ISBN: (纸本)9781728145341

Behavioural cloning, where a computer is taught to perform a task based on demonstrations, has been successfully applied to various video games and robotics tasks, with and without reinforcement learning. This also includes end-to-end approaches, where a computer plays a video game like humans do: by looking at the image displayed on the screen, and sending keystrokes to the game. As a general approach to playing video games, this has many inviting properties: no need for specialized modifications to the game, no lengthy training sessions and the ability to re-use the same tools across different games. However, related work includes game-specific engineering to achieve the results. We take a step towards a general approach and study the general applicability of behavioural cloning on twelve video games, including six modern video games (published after 2010), by using human demonstrations as training data. Our results show that these agents cannot match humans in raw performance but do learn basic dynamics and rules. We also demonstrate how the quality of the data matters, and how recording data from humans is subject to a state-action mismatch, due to human reflexes.

关键词： Games Cloning Training Task analysis Delays Tools signal resolution

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293页 << < 282 283 284 285 286 287 288 289 290 291 > >>

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：