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检索条件"任意字段=2023 International Conference on Image Processing and Computer Vision, IPCV 2023"

共 16199 条记录，以下是61-70 订阅

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Improving CCTV footage in computer vision Using Deep Learning Techniques

Improving CCTV footage in Computer Vision Using Deep Learnin...

引用

2023 international conference on Integrated Intelligence and Communication Systems, ICIICS 2023

作者： Rakshitha, C. Selvan, C. Reva University School of Cse Bengaluru India

ISBN: (纸本)9798350315455

The fields of computer vision and image processing, which deal with the analysis and modification of visual data like pictures and videos, are closely related. While computer vision focuses on tasks like object recognition and localization, image processing is dedicated to enhancing image quality through techniques like filtering and sharpening. Both are crucial as image quality impacts accurate analysis in various applications. Super-Resolution Generative Adversarial Networks (SRGANs) are a significant advancement in image processing, addressing the enhancement of low-resolution images into high-resolution ones. By employing an SRGAN framework with a generator, discriminator, and VGG19 feature extractor, remarkable super-resolution is achieved. SRGANs are valuable for improving image resolution in areas like scientific imaging, surveillance, and digital media. Higher resolution images enable finer detail detection, better object recognition, and enhanced visual experiences. The designed SRGAN demonstrated 85% training and 83.45% validation accuracy, with a testing accuracy of 80% on 1000 test images. Additionally, it achieved 84.55% testing accuracy on a low-resolution image dataset. This framework holds promise for various applications requiring superior image quality and resolution. © 2023 IEEE.

关键词： computer vision Discriminator Generator image processing Low-Resolution images Super-Resolution Generative Adversarial Networks (SRGANs) VGG19 Feature Extractor

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Randomrewardmechanisms (Loot Boxes): Behavioral Economics As A Regulatory Solution In Brazilian Law 17

Randomrewardmechanisms (Loot Boxes): Behavioral Economics As...

引用

17th international conference on Interfaces and Human computer Interaction 2023, IHCI 2023, the 17th international conference on computer Graphics, Visualization, computer vision and image processing 2023, CGVCVIP 2023 and 16th international conference on Game and Entertainment Technologies 2023, GET 2023

作者： Fantini, Laiane Maris Caetano PUC Minas. Centro DTIBR MG Belo Horizonte Brazil

ISBN: (纸本)9789898704498

The paper seeks to reflect on ways to create an effective regulation by understanding the aspects of random reward mechanisms in video games, also known as loot boxes. Players acquire digital assets of a game through microtransactions, and pays with in-game currency or real money. Among these digital assets, several games also offer loot boxes, which are systems of "surprise boxes" with a certain price but whose reward is unknown to the player (and is only revealed when the box is purchased and opened). A simple way of selling a digital asset has serious implications for players, mainly due to the similarity with gambling in making the reward relegated to chance. Also, adults and children players are encouraged to exhibit addictive behaviors, spending time and money without any control. Brazilian law does not have enough apparatus to protect consumers from these practices and banning loot boxes from the market does not seem to be the solution, as similar mechanisms could arise even worse. This way of marketing digital assets hides the real transaction costs and makes consumers make decisions based on heuristics, and that's why the Behavioral Economic Theory can offer better solutions to protect players. © 2023 Proceedings of the international conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer Graphics, Visualization, computer vision and image processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023. All rights reserved.

关键词： Human computer interaction

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EfficientNet-based diabetic retinopathy image classification

EfficientNet-based diabetic retinopathy image classification

引用

2023 international conference on computer Graphics, Artificial Intelligence, and Data processing, ICCAID 2023

作者： Feng, Liying Hebei University of Technology No. 8 Guangrong Road Dingzigu Hongqiao District Tianjin300401 China

ISBN: (纸本)9781510677685

Diabetic retinopathy is a common complication of diabetes that can lead to vision loss. Accurate detection of diabetic retinopathy is crucial for early intervention and treatment. This paper proposes a diabetic retinopathy detection method based on EfficientNet and optimizes the pooling layer. Experimental results conducted on the dataset provided by APTOS demonstrate that our approach achieves higher accuracy compared to other traditional methods. This study provides strong support for the early diagnosis and treatment of diabetic retinopathy and holds promising clinical applications. © 2024 SPIE.

关键词： image classification

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COMMON AND UNIQUE USER EXPERIENCE PROBLEMS ON E-COMMERCE WEBSITES 17

COMMON AND UNIQUE USER EXPERIENCE PROBLEMS ON E-COMMERCE WEB...

引用

作者： Hasan, Layla Faculty of Computing Universiti Teknologi Malaysia Johor Malaysia

ISBN: (纸本)9789898704498

This research evaluated the user experience (UX) on the top three most visited e-commerce websites in Malaysia, and identified common and unique issues which affected user experience while interacting with such sites. Specific user experience criteria were used in the evaluation, which was adapted from earlier research, and consists of 40 metrics. These metrics were used to evaluate the utilitarian and hedonic features on the websites. The evaluation was conducted using three methods: quantitative questionnaires, qualitative open-ended questions, and qualitative semi-structured interviews. Twenty students participated in this research and they identified ten common user experience problems related to the utilitarian features (e.g., illogical organisation of the websites' content and lack of presenting detailed information about the products);and three unique user experience problems related to the utilitarian features (i.e., not obvious navigation and lack of suggesting complementary products from other shops). Furthermore, the participants identified four common user experience problems related to the hedonic features (e.g., not visually attractive websites, not creative design, and a lack of desirable design elements which evoke users' emotions and gratitude);they also identified seven unique user experience problems on only one of the tested websites (i.e., the website was not motivating). © 2023 Proceedings of the international conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer Graphics, Visualization, computer vision and image processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023. All rights reserved.

关键词： Human computer interaction

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Proceedings of the international conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer Graphics, Visualization, computer vision and image processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023

Proceedings of the International Conferences on Interfaces a...

引用

ISBN: (纸本)9789898704498

The proceedings contain 36 papers. The topics discussed include: simple measurement of user response;is gesture-based interaction equally viable in manual and autonomous driving?;visual analytics for the marriage network in the Goryeo Dynasty, Korea;gradient pattern analysis applied for computer vision in medical ultrasound diagnosis;prototyping visualizations as a support for selecting representative models of petroleum reservoirs;how to teach programming with electronic games;a mobile conducting app with a switching beat-following algorithm;an augmented reality game for iOS smartphones;a gamified application for mitigating plastic pollution in coastal areas;and the impact of perceived challenge on narrative immersion in RPG video games: a preliminary study.

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Interactive image Segmentation with Cross-Modality vision Transformers

Interactive Image Segmentation with Cross-Modality Vision Tr...

引用

IEEE/CVF international conference on computer vision (ICCV)

作者： Li, Kun Vosselman, George Yang, Michael Ying Univ Twente Enschede Netherlands

ISBN: (纸本)9798350307443

Interactive image segmentation aims to segment the target from the background with the manual guidance, which takes as input multimodal data such as images, clicks, scribbles, polygons, and bounding boxes. Recently, vision transformers have achieved a great success in several downstream visual tasks, and a few efforts have been made to bring this powerful architecture to interactive segmentation task. However, the previous works neglect the relations between two modalities and directly mock the way of processing purely visual information with self-attentions. In this paper, we propose a simple yet effective network for click-based interactive segmentation with cross-modality vision transformers. Cross-modality transformers exploit mutual information to better guide the learning process. The experiments on several benchmarks show that the proposed method achieves superior performance in comparison to the previous state-of-the-art models. In addition, the stability of our method in term of avoiding failure cases shows its potential to be a practical annotation tool. The code and pretrained models will be released under https: //***/lik1996/iCMFormer.

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LeCA: In-Sensor Learned Compressive Acquisition for Efficient Machine vision on the Edge 23

LeCA: In-Sensor Learned Compressive Acquisition for Efficien...

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50th Annual international Symposium on computer Architecture (ISCA)

作者： Ma, Tianrui Boloor, Adith Jagadish Yang, Xiangxing Cao, Weidong Williams, Patrick Sun, Nan Chakrabarti, Ayan Zhang, Xuan Washington Univ St Louis MO 63110 USA Univ Texas Austin Austin TX USA Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9798400700958

With the rapid advances of deep learning-based computer vision (CV) technology, digital images are increasingly consumed, not by humans, but by downstream CV algorithms. However, capturing high-fidelity and high-resolution images is energy-intensive. It not only dominates the energy consumption of the sensor itself (i.e. in low-power edge devices), but also contributes to significant memory burdens and performance bottlenecks in the later storage, processing, and communication stages. In this paper, we systematically explore a new paradigm of in-sensor processing, termed "learned compressive acquisition" (LeCA). Targeting machine vision applications on the edge, the LeCA framework exploits the joint learning of a sensor autoencoder structure with the downstream CV algorithms to effectively compress the original image into low-dimensional features with adaptive bit depth. We employ column-parallel analog-domain processing directly inside the image sensor to perform the compressive encoding of the raw image, resulting in meaningful hardware savings, and energy efficiency improvements. Evaluated within a modern machine vision processing pipeline, LeCA achieves 4x, 6x, and 8x compression ratios prior to any digital compression, with minimal accuracy loss of 0.97%, 0.98%, and 2.01% on imageNet, outperforming existing methods. Compared with the conventional full-resolution image sensor and the state-of-the-art compressive sensing sensor, our LeCA sensor is 6.3x and 2.2x more energy-efficient while reaching a 2x higher compression ratio.

关键词： CMOS image sensor image compression autoencoder

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Synergistic image Encryption Using a Hybrid of Logistic, Tent, and Intermittent Chaotic Mappings 2

Synergistic Image Encryption Using a Hybrid of Logistic, Ten...

引用

2nd international conference on image processing, computer vision and Machine Learning, ICICML 2023

作者： Qu, Yicheng Qin, Zhibao Tsinghua International School Daoxiang Lake Beijing100194 China Communication University of China Beijing100024 China

ISBN: (纸本)9798350331417

The encryption of images is an essential component of ensuring data security in the digital age. Delving into chaotic mappings, our study unveils their robust potential for image encryption. In this paper, we propose a novel scheme for encryption-decryption by merging three chaotic mappings - Logistic, Tent, and Intermittent - into a single scheme. Our rigorous empirical evaluations, spanning histogram uniformity, entropy metrics, and key sensitivity, establish the unparalleled efficacy of our amalgamated approach. © 2023 IEEE.

关键词： chaotic mappings image encryptions Intermittent mapping Logistic mapping tent mapping

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A vision-like network for low-light image enhancement 2

A vision-like network for low-light image enhancement

引用

2nd international conference on image processing, computer vision and Machine Learning, ICICML 2023

作者： Huang, Zishen Li, Jindong Hu, Xiao Ji, Guangyi Guangzhou University School of Mechanical and Electrical Engineering Guangzhou China

ISBN: (纸本)9798350331417

Zero-shot learning is a popular strategy for low-light image enhancement, as it allows convolutional neural networks (CNNs) to be trained without paired data. However, existing zero-shot learning methods often lead to the loss of image details and noise amplification when processing images with extremely low illumination. To address this issue, a vision-like network is proposed, which is inspired by the human visual mechanism of "first the whole, then the part". This lightweight network has only 5349 parameters and is capable of retaining image details. Additionally, a non-reference loss function based on the median filtering algorithm is proposed to reduce information loss caused by rigid denoising. Experimental results show that our method outperforms existing zero-shot learning methods. © 2023 IEEE.

关键词： curve estimation low-light image enhancement noise suppression zero-shot learning

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image processing Method Based on MATLAB in the Application of Belt Tracking with Industrial Robot 13th

Image Processing Method Based on MATLAB in the Application o...

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13th international conference on computer Engineering and Networks (CENet)

作者： Tang Youan Zhao Lingyan Chen Gandong Shandong Jiaotong Univ Sch Construct Machinery Jinan Peoples R China

ISBN: (纸本)9789819992454;9789819992430;9789819992423

At present, the application of industrial robots combined with visual systems to achieve dynamic grasping materials of the belt is becoming increasingly widespread. Unlike the behavior of industrial robots grabbing after the belt stops, industrial robots dynamically tracking and grabbing materials on the belt can greatly improve production efficiency. For vision, processing distorted material images during high-speed movement and to obtain accurate coordinate points of materials is a key task to improve the accuracy of the belt tracking applications with industrial robot. Developing image processing algorithms based on MATLAB can, on the one hand, utilize existing software and hardware interface functions to improve development efficiency;On the other hand, autonomous and controllable image processing algorithms can be developed based on application requirements to maximize system accuracy.

关键词： Belt Dynamical tracking Industrial robots image processing

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