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检索条件"任意字段=2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023"

共 4812 条记录，以下是271-280 订阅

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Research on image processing System Based on computer Artificial Intelligence Technology 5

Research on Image Processing System Based on Computer Artifi...

引用

5th ieee international conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Chen, Xin Zhenjiang Vocational Technical College Zhenjiang China

ISBN: (纸本)9798350310603

This paper introduces the two-channel digital image processing technology. The system uses FPGA as its core processing unit. Infrared thermal imager and CCD camera were used for the shooting. The FPGA composed of programmable gate array realizes the pre-processing of the acquired image data and interacts with it. The video image processing of the two channels is completed, and the image features are extracted. Verilog language, built-in DSP core and NiosII processor are used to design the hardware. The experimental results show that this method has good real-time performance, good image processing effect, low cost and simple structure. © 2023 ieee.

关键词： Field programmable gate arrays (FPGA)

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A Review of Various image processing Techniques for UAV Based Photogrammetry

A Review of Various Image Processing Techniques for UAV Base...

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2023 international conference on IoT, Communication and Automation Technology, ICICAT 2023

作者： Kumari, Roshani Dubey, Deepam NIELIT VLSI Design Department of Electronics Gorakhpur India

ISBN: (纸本)9798350302820

Photogrammetry is a technology dealing with the extraction of information from pictures and making a three-dimensional view of it to get a precise and accurate picture. With the advancement of technology, the use of UAVs in image processing such as photogrammetry has extensively increased for various applications, like Farming, Foresting, Industrial Monitoring, GIS surveys, and Geographical mapping. In most of these applications, the images are captured and further processed to extract the data;hence, image processing becomes unavoidable. Also, UAVs, which perform autonomously and are powered by Artificial Intelligence, require fast and efficient onboard image processing for various applications. Computing efficiency is well associated with the power and battery time of UAVs. Thus, the researchers have focused on developing techniques and algorithms for image processing that can reduce computing time and power consumption, which will increase the efficiency of UAVs by reducing their weight and processing time. Here, in this survey, various constraints, and requirements of image processing for UAVs applications have been studied. Also, various image-processing techniques that can be used for UAV applications are compared in this work. © 2023 ieee.

关键词： Unmanned aerial vehicles (UAV)

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image Inpainting Using Deep Learning Techniques: A Review 5

Image Inpainting Using Deep Learning Techniques: A Review

引用

5th international conference on Control, Communication and Computing, ICCC 2023

作者： Haritha, L. Prajith, C.A. College of Engineering Trivandrum Department of Electronics and Communication Trivandrum India

ISBN: (纸本)9798350334128

image inpainting is a significant research area in the field of computer vision, with a diverse range of applications in image processing. Traditional image inpainting techniques proved to ineffective in generating better inpainted results, as they tend to produce inconsistent and multiple image semantics. Due to the advancement of Deep learning (DL) in recent years, this can be employed to address the issues with conventional image inpainting techniques. Currently, researches are mainly focused on image inpainting techniques based on deep learning using CNN, GAN etc. In this article, several deep learning based image inpainting techniques are been reviewed. © 2023 ieee.

关键词： Deep learning

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image TRANSLATION-BASED DENIABLE ENCRYPTION AGAINST MODEL EXTRACTION ATTACK 30

IMAGE TRANSLATION-BASED DENIABLE ENCRYPTION AGAINST MODEL EX...

引用

30th ieee international conference on image processing (ICIP)

作者： Chen, Yiling Yao, Yuanzhi Yu, Nenghai Univ Sci & Technol China Sch Cyber Sci & Technol Hefei Peoples R China Hefei Univ Technol Sch Comp Sci & Informat Engn Hefei Peoples R China

ISBN: (纸本)9781728198354

In cloud storage applications, data owners' original images are usually encrypted before being outsourced to the cloud for preserving data owners' privacy. However, in deep learning model-based image encryption methods, an adversary can conduct the model extraction attack to reveal the model parameters and thus restore the privacy information by obtaining numerous encrypted images. In this paper, we propose an image translation-based deniable encryption (ITDE) scheme to achieve encryption deniability and defend against model extraction attacks. Differing from traditional encryption methods in which encrypted images are visually meaningless, ITDE applies image translation to generate encrypted images in the form of human faces. Moreover, ITDE provides deniability for data owners to keep the encryption parameters private. To defend against model extraction attacks, the defense mechanism is introduced in our proposed ITDE to preserve deep learning models. Experimental results demonstrate the superiority of our proposed methods in terms of encryption deniability and privacy preservation.

关键词： Deniable Encryption image Translation Model Extraction Attack Data Poisoning Attack

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image STITCHING BASED ON MULTI-SCALE MESHES 30

IMAGE STITCHING BASED ON MULTI-SCALE MESHES

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30th ieee international conference on image processing (ICIP)

作者： Li, Yixuan Zhao, Haotian Jia, Qi Pu, Nan Dalian Univ Technol Int Sch Informat Sci Engn Dalian Peoples R China Peking Univ Sch Software & Microelect Beijing Peoples R China Univ Trento Sch Comp Sci Trento Italy

ISBN: (纸本)9781728198354

Generating high-quality stitching images with a natural structure is a challenging task in computer vision. Recent image stitching methods based on warps failed to suppress the distortion of the images. They often bend the salient lines in the image, which is inconsistent with human perception. In this paper, we succeed in proposing a novelty model called multi-perspective warps for natural image stitching which is related to the density of feature points in the images. With it we can get more precise matching results. Three new energy terms are developed to stitch quality to specify and balance the expected for aligning the vertices of the multi-scale mesh, which can constrain the transformation of the mesh. We also explore and introduce three feature point reconstruction algorithms to enrich the features in the images. Extensive experiments demonstrate that the proposed method outperforms most state-of-the-arts by effectively preserving the linear structure in the image and improving the robustness.

关键词： image stitching Multi-scale mesh Energy terms

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Large-to-small image Resolution Asymmetry in Deep Metric Learning 23

Large-to-small Image Resolution Asymmetry in Deep Metric Lea...

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23rd ieee/CVF Winter conference on applications of computer Vision (WACV)

作者： Suma, Pavel Tolias, Giorgos Czech Tech Univ Visual Recognit Grp Fac Elect Engn Prague Czech Republic

ISBN: (纸本)9781665493468

Deep metric learning for vision is trained by optimizing a representation network to map (non-)matching image pairs to (non-)similar representations. During testing, which typically corresponds to image retrieval, both database and query examples are processed by the same network to obtain the representation used for similarity estimation and ranking. In this work, we explore an asymmetric setup by light-weight processing of the query at a small image resolution to enable fast representation extraction. The goal is to obtain a network for database examples that is trained to operate on large resolution images and benefits from fine-grained image details, and a second network for query examples that operates on small resolution images but preserves a representation space aligned with that of the database network. We achieve this with a distillation approach that transfers knowledge from a fixed teacher network to a student via a loss that operates per image and solely relies on coupled augmentations without the use of any labels. In contrast to prior work that explores such asymmetry from the point of view of different network architectures, this work uses the same architecture but modifies the image resolution. We conclude that resolution asymmetry is a better way to optimize the performance/efficiency trade-off than architecture asymmetry. Evaluation is performed on three standard deep metric learning benchmarks, namely CUB200, Cars196, and SOP. Code: https://***/pavelsuma/raml

关键词： Measurement Knowledge engineering image resolution Databases image retrieval Estimation computer architecture

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Remote Sensing: A Comprehensive Overview of Principles and applications 10

Remote Sensing: A Comprehensive Overview of Principles and A...

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10th ieee Uttar Pradesh Section international conference on Electrical, Electronics and computer Engineering, UPCON 2023

作者： Tiwari, Shubham Kushwaha, Pradeep Kumar Saraswat, Arpit Gupta, Shubhi Vashisht, Swati Singh, Yuvraj Amity University Greater Noida India Amity University Greater Noida Department of Cse Greater Noida India Amity University Department of Cse Uttar Pradesh India Gl Baja Instt of Technology and Management Department of Cse Greater Noida India

ISBN: (纸本)9798350382471

Remote sensing technology has been a crucial tool for gathering information about the Earth's surface and atmosphere for many years, with applications spanning several fields such as agriculture, forestry, coastal zone management, and environmental monitoring. This article presents a comprehensive overview of remote sensing principles and their uses in various industries. The fundamental concepts of remote sensing, including electromagnetic radiation, sensors, platforms used for data collection, and image processing techniques, are discussed. Moreover, different types of remote sensing data, such as multispectral, hyperspectral, and SAR data, are explored along with their applications across several industries. Lastly, the challenges and possibilities for remote sensing technology are examined, and future prospects are discussed. © 2023 ieee.

关键词： Change Detection Geostationary Hyperspectral Imaging image Analysis Tracking

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Transliteration from Hindi to English Using image processing 3

Transliteration from Hindi to English Using Image Processing

引用

3rd ieee international conference on Intelligent Technologies, CONIT 2023

作者： Yadav, Mahima Kumar, Ishan Lovely Professional University Department of Computer Science and Engineering Phagwara India

ISBN: (纸本)9798350338607

Transliteration is the process of changing a word or a text from one script to another while keeping the phonetic and orthographic features of the source language. Transliteration is an important part of natural language processing, especially for communicating with people who speak different languages. This paper focuses on the transliteration of the Hindi language into the English language, as Hindi is the official language of India and there is a huge amount of data in Hindi that must be translated into English for regional and global use. It is essential to transliterate Hindi into English so that speakers of other languages can comprehend and communicate in Hindi. This paper describes a hybrid approach for transliteration from Hindi to English that includes image processing and a model trained with attention, as well as its applications in diverse fields. The system is evaluated using a dataset of Hindi text images, and the outcomes show that the proposed method improves existing transliteration systems in both, accuracy and speed. © 2023 ieee.

关键词： Machine learning

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Personalized image Generation for Color Vision Deficiency Population

Personalized Image Generation for Color Vision Deficiency Po...

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ieee/CVF international conference on computer Vision (ICCV)

作者： Jiang, Shuyi Liu, Daochang Li, Dingquan Xu, Chang Univ Sydney Sydney NSW Australia Peng Cheng Lab Shenzhen Peoples R China

ISBN: (纸本)9798350307184

Approximately, 350 million people, a proportion of 8%, suffer from color vision deficiency (CVD). While image generation algorithms have been highly successful in synthesizing high-quality images, CVD populations are unintentionally excluded from target users and have difficulties understanding the generated images as normal viewers do. Although a straightforward baseline can be formed by combining generation models and recolor compensation methods as the post-processing, the CVD friendliness of the result images is still limited since the input image content of recolor methods is not CVD-oriented and will be fixed during the recolor compensation process. Besides, the CVD populations can not be fully served since the varying degrees of CVD are often neglected in recoloring methods. Instead, we propose a personalized CVDfriendly image generation algorithm with two key characteristics: (i) generating CVD-oriented images aligned with the needs of CVD populations;(ii) generating continuous personalized images for people with various CVD degrees through disentangling the color representation based on a triple-latent structure. Quantitative and qualitative experiments indicate our proposed image generation model can generate practical and compelling results compared to the normal generation model and combination baselines on several datasets.

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ConvMixer-UNet: A Lightweight Network for Breast Lesion Segmentation in Ultrasound images 20

ConvMixer-UNet: A Lightweight Network for Breast Lesion Segm...

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20th ACS/ieee international conference on computer Systems and applications (AICCSA)

作者： AbdElhakem, Sara Basiony, Sohier Torki, Marwan Alexandria Univ Fac Engn Comp & Syst Engn Dept Alexandria Egypt

ISBN: (纸本)9798350319439

Breast cancer is one of the most common types of cancer among women. It occurs when abnormal cells in the breast grow and divide uncontrollably. Early diagnosis and treatment are crucial in preventing its spread to the rest of the body. In this paper, we propose a ConvMixer-UNet network for ultrasound image segmentation. The objective is to identify the lesion in the ultrasound image. We design our network that consists of convolutional layers at the early level and ConvMixer layers at the latent level. ConvMixer is an extremely simple and parameter-efficient module that incorporates depthwise and pointwise convolutional layers. This model was evaluated using a breast ultrasound dataset (BUSI);it achieved an improvement in the value of Intersection over Union (IoU). We achieved 68.17% IoU and 80.60% Dice score. These scores are obtained via careful tuning for the network hyperparameters. Quantitative and qualitative comparisons ensure the value of our proposed network. Moreover, ConvMixer-UNet is considered a lightweight network compared to the leading medical segmentation network UNet and its extensions. We show that our network provides a significant reduction in the number of parameters to only 1.77 M parameters, in contrast to UNet which has 31.1 M parameters.

关键词： ConvMixer UNet Medical image Segmentation BUSI dataset

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