检索结果-内蒙古大学图书馆

2nd international conference on Artificial Intelligence, Human-computer Interaction and Robotics, AIHCIR 2023

作者： Wang, ZhiQiang Joshi, Aryan Zhang, GuiYing Ren, WenJia Jia, Feng Sun, XiaoHang Tianjin University of Technology and Education Dept. of Information Tech & Engineering Tianjin China Tianjin Ai Shen de Si Technology Co. Ltd Dept. of Information Tech & Engineering Tianjin China

ISBN: (纸本)9798350360363

This research project explores a paradigm shift in perceptual enhancement by integrating a Unified Recognition Framework and vision-Language Pre-Training in three-dimensional image reconstruction. Through the synergy of advanced algorithms from computer vision & language processing, the project tries to enhance the precision and depth of perception in reconstructed images. This innovative approach holds the potential to revolutionize fields such as medical imaging, virtual reality, and computer-aided design, providing a comprehensive perspective on the intersection of multimodal data processing and perceptual advancement. The anticipated research outcomes are expected to significantly contribute to the evolution of technologies that rely on accurate and contextually rich three-dimensional reconstructions. Moreover, the research aims to reduce the constant need for new datasets by improving pattern recognition through 3D image patterning on backpropagation. This continuous improvement of vectors is envisioned to enhance the efficiency and accuracy of pattern recognition, contributing to the optimization of perceptual systems over time. © 2023 IEEE.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Research of reading system of the pointer instrument based on embedded system 2

Research of reading system of the pointer instrument based o...

引用

2nd international conference on computer vision, image, and Deep Learning

作者： Song, Peng Zhang, Chengwei Zhang, Mi Tongda College Nanjing University of Posts and Telecommunications Yangzhou China

ISBN: (数字)9781510646827

ISBN: (纸本)9781510646810

With the rapid change of society and the continuous development of science and technology, the application of instruments is more and more widely in all kinds of places from daily life to chemical power and aerospace. The pointer instruments in traditional industries are still widely used. But without changing the original equipment structure, the intelligent transformation is still an urgent research direction. The object of this paper is a kind of pointer pressure instrument used in industry. The purpose of this paper is to research the reading system of the pointer instrument based on embedded hardware platform and simple software algorithm. This paper designs an automatic reading system of the value indicated by the dial of the pointer instrument. The system uses embedded hardware devices and adopts the design idea of Linux + Qt + OpenCV. An open source, cross platform and relatively simple image processing algorithm is designed in it. Canny Edge detection, Hough-Circles detection and the Hough-Lines detection are combined in it. © 2021 SPIE.

关键词： image processing

来源：评论

学校读者我要写书评

暂无评论

Hybrid Design of Real-Time image processing Techniques for Multiple Biomedical Applications

Hybrid Design of Real-Time Image Processing Techniques for M...

引用

2nd international conference on Recent Advancement in computer, Communication and Computational Sciences (RACCCS)

作者： Paul, Ria Shandilya, Rahul Sharma, R. K. Natl Inst Technol Kurukshetra Sch VLSI Design & Embedded Syst Kurukshetra Haryana India

ISBN: (纸本)9789811073861;9789811073854

The computer vision has become an indispensable part in the fields of biomedical application and laboratory research in which images are processed and analyzed. In this article, we have presented a non-invasive real-time biomedical image processing design. The aim of the current research is to propose a hybrid design by using techniques such as watershed, Eulerian Video Magnification and morphological filters for multiple biomedical applications like detection of brain tumor, lung cancer, gallbladder stone, cataract, and measurement of pulse rate and its implementation using MATLAB. The proposed design can process different category of images and manipulate them to visualize and understand the defects clearly that is not visible to the human eyes.

关键词： Biomedical image processing Watershed Eulerian Video Magnification Non-invasive

来源：评论

学校读者我要写书评

暂无评论

Designing an Improved Deep Learning-Based Classifier for Breast Cancer Identification in Histopathology images 12

Designing an Improved Deep Learning-Based Classifier for Bre...

引用

12th Iranian/2nd international conference on Machine vision and image processing, MVIP 2022

作者： Babaahmadi, Amirreza Khalafi, Sahar Esfahani, Fatemeh Malekipour University of Tehran School of Mechanical Engineering College of Engineering Tehran Iran Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan Iran Concordia University Department of Mechanical Indistrial and Aerospace Engineering Montreal Canada

ISBN: (纸本)9781665412162

Cancer is a rampant phenomenon caused by uncontrollable cells that grow and spread throughout the body. Invasive Ductal Carcinoma 1 is the most common type of breast cancer, which can be fatal for females if not detected early. As a result, prompt diagnosis is critical to maximizing surveillance rates and, in the meantime, minimizing long-term mortality rates. Nowadays, modern computer vision and deep learning techniques have transformed the medical image analysis arena. computer vision application in medical image analysis has provided us with remarkable results, enhanced accuracy, and reduced costs. The main purpose of designing a new algorithm to detect unusual patches of breast images, was to acquire both high accuracy and low computational cost, simultaneously. Therefore, a novel architecture has been designed by utilizing Xception and *** new algorithm achieves 93.4% balanced accuracy and 94.8% for F1-Score, which outperforms previously published algorithms for identifying IDC histopathology images that use deep learning techniques. © 2022 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Phone based Video processing Aimed at Outdoor Guidance for the Visually Impaired 18

Phone based Video Processing Aimed at Outdoor Guidance for t...

引用

2nd international conference on Information System and Data Mining (ICISDM)

作者： Langenkamp, Stephen P. P. C. Abid, Muhammad Rizwan Florida Polytech Univ Lakeland FL 33805 USA

ISBN: (纸本)9781450363549

This paper discusses an outdoor guidance system that can be implemented on a smartphone. The purpose of such a system would be to assist the blind or visually impaired. The system will be able to detect the ground, find obstacles, and notify the user when the obstacle is close enough to constitute a tripping hazard. This work uses a novel semantic segmentation technique and proposes an alternate method for positioning the phone for better fall prevention techniques.

关键词： computer vision Handicap Assistance Phone Application image Segmentation Video Analysis Floor Detection Fall Prevention

来源：评论

学校读者我要写书评

暂无评论

Scene reconstruction with sparse range information 2

Scene reconstruction with sparse range information

引用

2nd Canadian conference on computer and Robot vision, CRV 2005

作者： Chen, Guangyi Dudek, G. Torres-Mendez, L.A. Center for Intelligence Machines McGill Univ. MontrealQCH3A2A7 Canada

ISBN: (纸本)0769523196

This paper addresses an approach to scene reconstruction by inferring missing range data in a partial range map based on intensity image and sparse initial range data. It is assumed that the initial known range data is given on a number of scan lines one pixel width. This assumption is natural for a range sensor to acquire range data in a 3D real world environment. Both edge information of the intensity image and linear interpolation of the range data are used. Experiments show that this method gives very good results in inferring missing range data. It outperforms both the previous method and bilinear interpolation when a very small percentage of range data is known. © 2005 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Towards objective quality assessment of image registration results

Towards objective quality assessment of image registration r...

引用

2nd international conference on computer vision Theory and Applications, VISAPP 2007

作者： Möller, Birgit Garcia, Rafael Posch, Stefan Department of Electronics Informatics and Automation University of Girona Campus Montilivi Girona 17003 Spain Institute of Computer Science Martin-Luther-University Halle-Wittenberg Von-Seckendorff-Platz 1 06099 Halle/Saale Germany

Geometric registration of visual images is a fundamental intermediate processing step in a wide variety of computer vision applications that deal with image sequence analysis. 2D motion recovery and mosaicing, 3D scene reconstruction and also motion detection approaches strongly rely on accurate registration results. However, automatically assessing the overall quality of a registration is a challenging task. In particular, optimization criteria used in registration are not necessarily closely linked to the final quality of the result and often show a lack of local sensitivity. In this paper we present a new approach for an objective quality metric in 2D image registration. The proposed method is based on local structure analysis and facilitates voting-techniques for error pooling, leading to an objective measure that correlates well with the visual appearance of registered images. Since observed differences are furthermore classified in more detail according to various underlying error sources, the new measure not only yields a suitable base for objective quality assessment, but also opens perspectives towards an automatic and optimally adjusted correction of errors.

关键词： image registration

来源：评论

学校读者我要写书评

暂无评论

Effect Of image Colourspace On Performance Of Convolution Neural Networks 2

Effect Of Image Colourspace On Performance Of Convolution Ne...

引用

2nd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Reddy, K. Sumanth Singh, Upasna Uttam, Prakash K. DIAT DU Pune Dept Mech Engn Pune Maharashtra India DIAT DU Pune Dept Comp Engn Pune Maharashtra India R&D Engn DRDO Pune Electro Mech Syst Grp Pune Maharashtra India

ISBN: (纸本)9781509037049

Recently the term Deep Learning has been creating a lot of interest in the fields of Artificial Intelligence, computer vision and Natural Language processing. And especially the Convolution Neural Networks (CNN) are giving state of art results in image recognition, scene understanding, object detection and image description etc. Generally in CNN the processing of images is done in RGB colourspace even though we have many other colourspaces available. In this paper we try to understand the effect of image colourspace on the performance of CNN models in recognizing the objects present in the image. We evaluate this on CIFAR10 dataset, by converting all the original RGB images into four other colourspaces like HLS, HSV, LUV, YUV etc. To compare results we have trained AlexNet with fixed set of parameters on all five colourspaces, including RGB. We have observed that LUV colourspace is the best alternative to RGB colourspace to use with CNN models with almost equal performance on the test set of CIFAR10 dataset. While YUV colourspace is the worst to use with CNN models.

关键词： Convolution Neural Networks Colourspace CIFAR10 Object Recognition

来源：评论

学校读者我要写书评

暂无评论

Oracle Bone Script Similiar Character Screening Approach Based on Simsiam Contrastive Learning and Supervised Learning 2

Oracle Bone Script Similiar Character Screening Approach Bas...

引用

2nd international conference on Algorithm, image processing and Machine vision, AIPMV 2024

作者： Weng, Xinying Li, Yifan Hao, Shuaidong Hou, Jialiang College of Computer and Information Engineering Henan Normal University Henan Xinxiang China

ISBN: (纸本)9798350390254

This project proposes a new method that uses fuzzy comprehensive evaluation method to integrate ResN et-50 self- supervised and Rep Vggsupervised learning. The source image dataset HWOBC oracle is taken as input, the target image is selected, and finally the most similar image is output in turn without any manual intervention. The same feature encoding method is not used for images of different modalities. Before the model training, the image data is preprocessed, and the image is enhanced by random rotation processing, self-square graph equalization theory algorithm, and gamma transform, which effectively enhances the key feature learning. Finally, the fuzzy comprehensive evaluation method is used to combine the results of supervised training and unsupervised training, which can better solve the 'most similar' problem that is difficult to quantify. At present, there are many unknown oracle-bone inscriptions waiting for us to crack. Contacting with the glyphs can provide new ideas for cracking. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Making the V in VQA Matter: Elevating the Role of image Understanding in Visual Question Answering

引用

international JOURNAL OF computer vision 2019年第4期127卷 398-414页

作者： Goyal, Yash Khot, Tejas Agrawal, Aishwarya Summers-Stay, Douglas Batra, Dhruv Parikh, Devi Georgia Tech Atlanta GA 30332 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Army Res Lab Adelphi MD USA Facebook AI Res Menlo Pk CA USA

The problem of visual question answering (VQA) is of significant importance both as a challenging research question and for the rich set of applications it enables. In this context, however, inherent structure in our world and bias in our language tend to be a simpler signal for learning than visual modalities, resulting in VQA models that ignore visual information, leading to an inflated sense of their capability. We propose to counter these language priors for the task of VQA and make vision (the V in VQA) matter! Specifically, we balance the popular VQA dataset (Antol et al., in: ICCV, 2015) by collecting complementary images such that every question in our balanced dataset is associated with not just a single image, but rather a pair of similar images that result in two different answers to the question. Our dataset is by construction more balanced than the original VQA dataset and has approximately twice the number of image-question pairs. Our complete balanced dataset is publicly available at http://***/ as part of the 2nd iteration of the VQA Dataset and Challenge (VQA v2.0). We further benchmark a number of state-of-art VQA models on our balanced dataset. All models perform significantly worse on our balanced dataset, suggesting that these models have indeed learned to exploit language priors. This finding provides the first concrete empirical evidence for what seems to be a qualitative sense among practitioners. We also present interesting insights from analysis of the participant entries in VQA Challenge 2017, organized by us on the proposed VQA v2.0 dataset. The results of the challenge were announced in the 2nd VQA Challenge Workshop at the IEEE conference on computer vision and Pattern Recognition (CVPR) 2017. Finally, our data collection protocol for identifying complementary images enables us to develop a novel interpretable model, which in addition to providing an answer to the given (image, question) pair, also provides a counter-example ba

关键词： Visual question answering VQA VQA challenge

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：