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

17,661 篇 会议
259 册 图书
190 篇 期刊文献
1 篇 学位论文

馆藏范围

18,110 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

10,534 篇 工学
- 6,233 篇 计算机科学与技术...
- 4,015 篇 电气工程
- 3,829 篇 控制科学与工程
- 2,908 篇 软件工程
- 1,924 篇 信息与通信工程
- 1,554 篇 光学工程
- 1,406 篇 机械工程
- 997 篇 仪器科学与技术
- 583 篇 电子科学与技术（可...
- 549 篇 生物医学工程（可授...
- 433 篇 生物工程
- 232 篇 材料科学与工程（可...
- 195 篇 交通运输工程
- 163 篇 安全科学与工程
- 154 篇 化学工程与技术
- 139 篇 力学（可授工学、理...
- 115 篇 建筑学
- 110 篇 土木工程
- 104 篇 航空宇航科学与技...
3,400 篇 理学
- 2,548 篇 物理学
- 805 篇 数学
- 486 篇 生物学
- 295 篇 系统科学
- 209 篇 统计学（可授理学、...
- 134 篇 化学
1,654 篇 医学
- 1,577 篇 临床医学
- 185 篇 基础医学(可授医学...
761 篇 管理学
- 582 篇 管理科学与工程(可...
- 190 篇 图书情报与档案管...
- 120 篇 工商管理
107 篇 农学
78 篇 法学
43 篇 经济学
42 篇 教育学
39 篇 艺术学
37 篇 军事学
18 篇 文学

主题

2,736 篇 computer vision
1,685 篇 cameras
1,489 篇 signal processin...
1,441 篇 robot vision sys...
1,355 篇 image processing
1,173 篇 robot sensing sy...
912 篇 signal processin...
874 篇 mobile robots
839 篇 feature extracti...
769 篇 machine vision
549 篇 image segmentati...
504 篇 object detection
440 篇 visualization
424 篇 deep learning
409 篇 robustness
393 篇 estimation
367 篇 stereo vision
358 篇 navigation
343 篇 training
319 篇 robot kinematics

机构

83 篇 centre for visio...
63 篇 xi an jiao tong ...
54 篇 centre for visio...
37 篇 school of electr...
36 篇 centre for visio...
29 篇 carnegie mellon ...
28 篇 chinese acad sci...
27 篇 shanghai jiao to...
27 篇 center for machi...
27 篇 university of ch...
23 篇 centre for visio...
23 篇 harbin inst tech...
21 篇 univ chinese aca...
21 篇 nanyang technol ...
17 篇 centre for visio...
16 篇 university of sc...
16 篇 tsinghua univers...
13 篇 chinese acad sci...
13 篇 univ sci & techn...
13 篇 chinese univ hon...

作者

52 篇 j. kittler
40 篇 josef kittler
28 篇 nakadai kazuhiro
19 篇 anil fernando
18 篇 wang wei
15 篇 chen chen
14 篇 yang yang
14 篇 nascimento jacin...
13 篇 jing zhang
13 篇 liu yang
13 篇 sun fuchun
12 篇 sun lining
12 篇 hansung kim
11 篇 zhang lei
11 篇 bartolozzi chiar...
11 篇 hong liu
10 篇 wang lei
10 篇 li yang
10 篇 aguiar pedro m. ...
10 篇 qiuqiang kong

语言

17,927 篇 英文
86 篇 中文
84 篇 其他
12 篇 土耳其文
3 篇 俄文
2 篇 西班牙文

检索条件"任意字段=International Conference on Robot Vision and Signal Processing"

共 18111 条记录，以下是341-350 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：

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Wang, Qi Yu, Wenxin Che, Lu Liu, Chang Zhang, Zhiqiang Gong, Jun Chen, Peng Southwest Univ Sci & Technol Mianyang Peoples R China Southwest Univ Sci & Technol Tianfu Inst Res & Innovat Mianyang Peoples R China Sichuan Civil Mil Integrat Inst Chengdu Peoples R China Instrumentat Technol & Econ Inst Beijing Peoples R China Southwest Automat Res Inst San Antonio TX USA Chengdu Hongchengyun Technol Co Ltd Chengdu Peoples R China

ISBN: (纸本)9798350344868;9798350344851

In this paper, we propose a novel and efficient method for knowledge distillation, which is structurally simple and requires negligible computation overhead. Our method includes three modules. The first module is the calibrated mask, which avoids the teacher model's incorrect representation to disturb the student model's training;the second module and the third module improve the performance of the student model by the similarity of the sample and the process, respectively. The student model attains better performance in qualitative and quantitative evaluation through the judicious amalgamation of these three modules. Our method is experimented with through rigorous validation of canonical datasets, including CIFAR-100 and TinyImageNet. The experimental corroboration conclusively attests to the better performance of our method, soaring above the extant most state-of-the-art on both subjective and objective dimensions.

关键词： Computer vision Deep Learning Classification Model Compression Knowledge Distillation

来源：评论

学校读者我要写书评

暂无评论

CLIPRERANK: AN EXTREMELY SIMPLE METHOD FOR IMPROVING AD-HOC VIDEO SEARCH 49

CLIPRERANK: AN EXTREMELY SIMPLE METHOD FOR IMPROVING AD-HOC ...

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Chen, Aozhu Zhou, Fangming Wang, Ziyuan Li, Xirong Renmin Univ China Beijing Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Ad-hoc Video Search (AVS) enables users to search for unlabeled video content using on-the-fly textual queries. Current deep learning-based models for AVS are trained to optimize holistic similarity between short videos and their associated descriptions. However, due to the diversity of ad-hoc queries, even for a short video, its truly relevant part w.r.t. a given query can be of shorter duration. In such a scenario, the holistic similarity becomes suboptimal. To remedy the issue, we propose in this paper CLIPRerank, a fine-grained re-scoring method. We compute cross-modal similarities between query and video frames using a pre-trained CLIP model, with multi-frame scores aggregated by max pooling. The fine-grained score is weightedly added to the initial score for search result reranking. As such, CLIPRerank is agnostic to the underlying video retrieval models and extremely simple, making it a handy plug-in for boosting AVS. Experiments on the challenging TRECVID AVS benchmarks (from 2016 to 2021) justify the effectiveness of the proposed strategy. CLIPRerank consistently improves the TRECVID top performers and multiple existing models including SEA, W2VV++, Dual Encoding, Dual Task, LAFF, CLIP2Video, TS2-Net and X-CLIP. Our method also works when substituting BLIP-2 for CLIP.

关键词： Ad-hoc video search Large vision language models Video search reranking

来源：评论

学校读者我要写书评

暂无评论

FAST INTRA MODE PREDICTION ALGORITHMS FOR SCBS IN VVC SCC 49

FAST INTRA MODE PREDICTION ALGORITHMS FOR SCBS IN VVC SCC

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Wang, Dayong Deng, Yishen Li, Weisheng Lu, Xin Dufaux, Frederic Hang, Bo Zhu, Ce Chongqing Univ Posts & Telecommun Key Lab Big Data Intelligent Comp Chongqing Peoples R China Wuzhou Univ Guangxi Key Lab Machine Vision & Intelligent Cont Wuzhou Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Image Cognit Chongqing Peoples R China De Montfort Univ Fac Comp Engn & Media CEM Leicester Leics England Univ Paris Saclay CNRS CentraleSupelec Lab Signaux & Syst Gif Sur Yvette France Hubei Univ Arts & Sci Comp Sch Xiangyang Peoples R China Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Versatile Video Coding (VVC) now supports Screen Content Coding (SCC) by integrating two efficient coding modes: Intra Block Copy (IBC) and Palette (PLT). However, the numerous modes and the Quad-Tree Plus Multi-Type Tree (QTMT) structure inherent to VVC contribute to a very high coding complexity. To effectively reduce the computational complexity of VVC SCC, we propose a fast Intra mode prediction algorithm for VVC SCC. More specifically, we first use the difference of minimum Sum of Absolute Transformed Differences (SATD) value of four Directional Modes (DMs) of Intra and the SATD value of the IBC-merge mode to determine whether to early skip Intra checking. Subsequently, we use a decision tree to determine whether to early terminate the checking after block differential pulse coded modulation (BDPCM). Finally, we employ a decision tree to determine whether to early skip multiple transform selection (MTS) and low frequency non-separable transform (LFNST) checking. The results demonstrate that our algorithm achieves an average encoding time reduction of 34.34% with a negligible Bjontegaard delta bitrate increase of 0.46%.

关键词： Screen Content Coding (SCC) Versatile Video Coding (VVC) Bayesian model decision tree Intra mode

来源：评论

学校读者我要写书评

暂无评论

Semi-Automatic Labeling for Action Recognition by Diversity Preserving Sampling

Semi-Automatic Labeling for Action Recognition by Diversity ...

引用

2025 IEEE international conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Ando, Ryuhei Shibata, Takashi Takahashi, Toru NEC Corporation Japan

ISBN: (纸本)9798350368741

Deep learning for action recognition is an important technology for understanding videos. However, collecting video training dataset for deep learning model with low cost while maintaining enough diversity is challenging. In this paper, we propose a semi-automatic labeling framework for action recognition by diversity-preserving sampling. The proposed framework utilizes a pre-trained vision-language model (VLM) to search through video clips to filter data that matches the text that describes the appropriate context for the target action. Since this simple approach by VLM tends to lack diversity, our framework is also equipped with diversity-preserving sampling that consists of two sampling strategies. One is confidence-based weighted sampling, which is based on action class confidence obtained from VLM, and the other is isolate-constraint-based weighted sampling, which samples points that are far apart in the text-image feature space. We conduct experiments to demonstrate that the proposed approach efficiently collects data with variations that could train a better action recognition model than the baseline. © 2025 IEEE.

关键词： action recognition labeling framework text-video retrieval vision-language model

来源：评论

学校读者我要写书评

暂无评论

Hazard Hunter: A Low Cost Search and Rescue robot

Hazard Hunter: A Low Cost Search and Rescue Robot

引用

2024 international conference on signal processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Saha, Arajit Islam, Zahidul Mondal, Shuvra American International University-Bangladesh Dept. of EEE Dhaka Bangladesh

ISBN: (纸本)9798331540685

Rescue operations are among the most vital pillars of disaster management. The duties associated with rescue operations or monitoring in such situations are exceedingly risky. Besides, human participation in such endeavors is invariably hazardous. As a result, as the probability of human error and the need for manual labor diminished, robot involvement gained importance. On the contrary, before human rescue teams embrace robotic assistance, individuals must be confident that it will benefit them rather than hinder them. Considering these issues, an affordable search and rescue robot (SARR) 'Hazard Hunter' is proposed and designed to suit developing nations like Bangladesh. This robot is cheap and straightforward to build from common components. Human rescuers may easily exploit the robot's information without any robotic expertise. One notable benefit of this robot is that it can perform remote operations via a wireless way. Sensors, along with a camera module, are incorporated into the design of the automaton to provide real-time information about the terrain around it and enable adequate surveillance. As required, the user may add or remove sensors and access those sensor's readings via web-based monitoring. The development of a user-friendly IP address-based webpage accomplishes the movement of the robot and the acquisition of sensor data for environmental monitoring. It provides continuous thermal, visual, and ambient sensory data from the catastrophe site to the online dashboard. It can also find live people amid debris and communicate with rescuers. The proposed rescue robot has undergone extensive experiments and performance-based evaluation. It will effectively carry out its responsibilities in any critical circumstance. © 2024 IEEE.

关键词： Disaster prevention

来源：评论

学校读者我要写书评

暂无评论

Floor Cleaning robot with Android-Based Voice Command 9

Floor Cleaning Robot with Android-Based Voice Command

引用

9th international conference on Wireless Communications, signal processing and Networking, WiSPNET 2024

作者： Midhun, V.S. Pondurai, M. Vairaprakash, S. Ramco Institute of Technology ECE Department Tamil Nadu Rajapalayam India

ISBN: (纸本)9798350350845

The Voice-Controlled Floor Cleaning robot with Android Application Integration presents an innovative solution to streamline household cleaning tasks. By harnessing the power of voice command technology and mobile connectivity, this project aims to revolutionize the way floors are cleaned in modern homes. The system enables users to remotely access and control the robot from any location, eliminating the need for manual intervention and saving valuable time. Through a dedicated Android application, users can issue voice commands to the robot via their smartphones or tablets. These commands are transmitted to the robot's microcontroller unit, where they are interpreted and executed as predefined functions. This seamless interaction between the user and the robot allows for effortless control over the cleaning process, enhancing user convenience and efficiency. The robot's functionality encompasses a range of cleaning tasks, including sweeping, mopping, and vacuuming, catering to various floor surfaces and cleaning requirements. Equipped with sensors and navigation systems, the robot can autonomously navigate the cleaning area, avoiding obstacles and optimizing cleaning patterns for thorough and effective results. Overall, the Voice-Controlled Floor Cleaning robot with Android Application Integration offers a cutting-edge solution to simplify and expedite floor cleaning tasks. By integrating voice command technology with mobile connectivity, this project sets a new standard for smart home cleaning systems, promising a cleaner, more convenient living environment for users. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

来源：评论

学校读者我要写书评

暂无评论

Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-Based vision 17th

Optimising Graph Representation for Hardware Implementation ...

引用

17th international Workshop on Design and Architecture for signal and Image processing (DASIP)

作者： Jeziorek, Kamil Wzorek, Piotr Blachut, Krzysztof Pinna, Andrea Kryjak, Tomasz AGH Univ Krakow Dept Automat Control & Robot Embedded Vis Syst Grp Krakow Poland Sorbonne Univ LIP6 CNRS F-75005 Paris France

ISBN: (纸本)9783031628733;9783031628740

Event-based vision is an emerging research field involving processing data generated by Dynamic vision Sensors (neuromorphic cameras). One of the latest proposals in this area are Graph Convolutional Networks (GCNs), which allow to process events in its original sparse form while maintaining high detection and classification performance. In this paper, we present the hardware implementation of a graph generation process from an event camera data stream, taking into account both the advantages and limitations of FPGAs. We propose various ways to simplify the graph representation and use scaling and quantisation of values. We consider both undirected and directed graphs that enable the use of PointNet convolution. The results obtained show that by appropriately modifying the graph representation, it is possible to create a hardware module for graph generation. Moreover, the proposed modifications have no significant impact on object detection performance, only 0.08% mAP less for the base model and the N-Caltech data set. Finally, we describe the proposed hardware architecture of the graph generation module.

关键词： graph representation GCN event cameras object detection FPGA

来源：评论

学校读者我要写书评

暂无评论

SelaFD:Seamless Adaptation of vision Transformer Fine-tuning for Radar-based Human Activity Recognition

SelaFD:Seamless Adaptation of Vision Transformer Fine-tuning...

引用

2025 IEEE international conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Wang, Yijun Wang, Yong Xu, Chendong Yao, Shuai Wu, Qisong Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China

ISBN: (纸本)9798350368741

Human Activity Recognition (HAR) such as fall detection has become increasingly critical due to the aging population, necessitating effective monitoring systems to prevent serious injuries and fatalities associated with falls. This study focuses on fine-tuning the vision Transformer (ViT) model specifically for HAR using radar-based Time-Doppler signatures. Unlike traditional image datasets, these signals present unique challenges due to their non-visual nature and the high degree of similarity among various activities. Directly fine-tuning the ViT with all parameters proves suboptimal for this application. To address this challenge, we propose a novel approach that employs Low-Rank Adaptation (LoRA) fine-tuning in the weight space to facilitate knowledge transfer from pre-trained ViT models. Additionally, to extract fine-grained features, we enhance feature representation through the integration of a serial-parallel adapter in the feature space. Our innovative joint fine-tuning method, tailored for radar-based Time-Doppler signatures, significantly improves HAR accuracy, surpassing existing state-of-the-art methodologies in this domain. Our code is released at https://***/wangyijunlyy/SelaFD. © 2025 IEEE.

关键词： Fine-Tuning Human Activity Recognition Time-Doppler vision Transformer

来源：评论

学校读者我要写书评

暂无评论

Reward Generation via Large vision-Language Model in Offline Reinforcement Learning

Reward Generation via Large Vision-Language Model in Offline...

引用

2025 IEEE international conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Lee, Younghwan Luu, Tung M. Lee, Donghoon Yoo, Chang D. Electrical Engineering KAIST Daejeon Korea Republic of Robotics Program KAIST Daejeon Korea Republic of

ISBN: (纸本)9798350368741

In offline reinforcement learning (RL), learning from fixed datasets presents a promising solution for domains where real-time interaction with the environment is expensive or risky. However, designing dense reward signals for offline dataset requires significant human effort and domain expertise. Reinforcement learning with human feedback (RLHF) has emerged as an alternative, but it remains costly due to the human-in-the-loop process, prompting interest in automated reward generation models. To address this, we propose Reward Generation via Large vision-Language Models (RG-VLM), which leverages the reasoning capabilities of LVLMs to generate rewards from offline data without human involvement. RG-VLM improves generalization in long-horizon tasks and can be seamlessly integrated with the sparse reward signals to enhance task performance, demonstrating its potential as an auxiliary reward signal. © 2025 IEEE.

关键词： Large vision-Language Model Offline Reinforcement Learning Reward Labeling

来源：评论

学校读者我要写书评

暂无评论

MUSICLDM: ENHANCING NOVELTY IN TEXT-TO-MUSIC GENERATION USING BEAT-SYNCHRONOUS MIXUP STRATEGIES 49

MUSICLDM: ENHANCING NOVELTY IN TEXT-TO-MUSIC GENERATION USIN...

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Chen, Ke Wu, Yusong Liu, Haohe Nezhurina, Marianna Berg-Kirkpatrick, Taylor Dubnov, Shlomo Univ Calif San Diego UCSD La Jolla CA 92093 USA Univ Montreal Quebec Artificial Intelligence Inst Mila Montreal PQ Canada Univ Surrey Ctr Vision Speech & Signal Proc Surrey England LAION Hamburg Germany

ISBN: (纸本)9798350344868;9798350344851

Diffusion models have shown promising results in cross-modal generation tasks, including text-to-image and text-to-audio generation. However, generating music, as a special type of audio, presents unique challenges due to limited availability of music data and sensitive issues related to copyright and plagiarism. In this paper, to tackle these challenges, we first construct a state-of-the-art text-to-music model, MusicLDM, that adapts Stable Diffusion and AudioLDM architectures to the music domain. Then, to address the limitations of training data and to avoid plagiarism, we leverage a beat tracking model and propose two different mixup strategies for data augmentation: beat-synchronous audio mixup and beat-synchronous latent mixup, which recombine training audio directly or via a latent embeddings space, respectively. Such mixup strategies encourage the model to interpolate between musical training samples and generate new music within the convex hull of the training data, making the generated music more diverse while still staying faithful to the corresponding style. In addition to popular evaluation metrics, we design several new evaluation metrics based on CLAP score to demonstrate that our proposed MusicLDM and beat-synchronous mixup strategies improve both the quality and novelty of generated music, as well as the correspondence between input text and generated music.

关键词： Music Generation Audio Synthesis Diffusion Model Text-to-Music

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 << < 31 32 33 34 35 36 37 38 39 40 > >>

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：