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A Scale-Arbitrary Network for Chinese Painting Super-Resolution 23

A Scale-Arbitrary Network for Chinese Painting Super-Resolut...

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6th International conference on Information Science and Systems, ICISS 2023

作者： Wu, Yuekun Zhou, Yue Xu, Kun State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications China

ISBN: (纸本)9798400708206

image super-resolution (SR) plays a crucial role in enhancing low-resolution (LR) images to high-resolution (HR) images. In the context of Chinese painting, SR is of great significance for cultural presentation and post-processing. However, existing methods for super-resolution are limited to specific integer scale factors, and when it comes to the super-resolution of Chinese painting with large scales, the preservation of intricate textural details is compromised. In this paper, we propose a novel super-resolution network capable of handling arbitrary scale factors and preserving rich textural details for Chinese painting. Our network integrates the Meta-RCAN framework with a Scale-Aware Feature Learning Module to achieve superior effects. Furthermore, we introduce Haar loss and degradation loss to better preserve high-frequency features and enhance realistic details and textures. We also introduce global residual learning and fusion to obtain more shallow features. To facilitate our research, we create a large-scale high-performance dataset, Chi-Paint-HD, specifically designed for Chinese painting images. Experimental results demonstrate that our model achieves superior super-resolution performance for arbitrary scale factors, outperforming others models in terms of peak signal-To-noise ratio (PSNR), structural similarity (SSIM), and overcoming over-smoothing issues. Additionally, our model achieves excellent quantitative evaluation results and high-quality visual performance for integer scale factors, surpassing previous models that are limited to specific scales. © 2023 ACM.

关键词： Textures

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ACIGS: An automated large-scale crops image generation system based on large visual language multi-modal models

ACIGS: An automated large-scale crops image generation syste...

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IEEE communications Society conference on Sensor and Ad Hoc communications and Networks (SECON)

作者： Bolong Liu Hao Zhang Jie Liu Qiang Wang Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Computer Science and Technology Harbin Institute of Technology (ShenZhen) ShenZhen China

Smart agriculture requires an extensive convergence of information technology and agriculture. Attaining intelligence mandates an enormous amount of data to train models. However, it is challenging to acquire a large number of crop image data, limiting the application and growth of computer vision technology in agriculture. To address this problem, we designed a crop image generation system that combines a large language model with visual language multi-modal large models to augment the scale, variety, and resolution of crop image data. First, the system inputs existing real crop images into the visual language multimodal model to extract features and represent crop images in text form. Then, the system passes the crop text representation to the language model for cleaning and processing, which generates prompts to create crop images. The prompts are input into the visual language multi-modal model to generate crop images based on text representation of crops. The resulting crop images undergo image quality evaluation in the visual language multimodal model, and high-quality crop images are saved to the crop image dataset based on the quality evaluation. These steps lead to the formation of the final generated crop image dataset. The experimental results indicate that the crop images generated using the proposed system are similar to but different from the example images. This characteristic enables the expansion of crop data while circumventing redundancy and allowing for resolution control, which is crucial for dense segmentation tasks. Using this method, the existing data can be enlarged up to 7.5 times.

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visual Understanding and Navigation for the visually Impaired Using image Captioning

Visual Understanding and Navigation for the Visually Impaire...

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Cognitive Computing in Engineering, communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International conference on

作者： Jitesh Uikey Ishan Undre Urvish Vasani Aman Shaikh Riddhi Mirajkar Jayashree Bagade Department of Information Technology Vishwakarma Institute Of Information Technology Pune India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

visually impaired people face problems with independent navigation due to limited visual information. Facing significant challenges, they often travel with an assistant or their relative. This project introduces an approach, increasing the independence of a blind user by developing new software solutions. The proposed system employs DenseNet201 for feature extraction and Long Short-Term Memory (LSTM) networks for generating accurate, context-aware captions. These captions are converted into real-time auditory descriptions using the gTTS library, enabling users to interpret and navigate their environment confidently. Evaluated on the Flickr8k dataset, the system achieved a BLEU score of 0.721, demonstrating its ability to generate high-quality captions. The system's architecture is designed to balance accuracy, efficiency, and user accessibility. Additionally, the system incorporates a modular architecture optimized for computational efficiency and scalability. Future work includes exploring wearable technology for continuous real-time feedback, integrating advanced natural language processing (NLP) models for richer contextual understanding, and enhancing its applicability in complex indoor and outdoor environments. This approach represents a significant step toward empowering visually impaired individuals with improved mobility and environmental awareness.

关键词： Deep learning visualization Navigation Computer architecture Feature extraction Natural language processing Real-time systems Convolutional neural networks Wearable devices Long short term memory

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Adaptive SLIC-Based Fuzzy Intensity Dissimilarity Thresholding for Color image Segmentation

Adaptive SLIC-Based Fuzzy Intensity Dissimilarity Thresholdi...

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Natural Language processing (ICNLP), International conference on

作者： Lan Rong Feng Danlin Zhao Feng Yu Haiyan Zhang Lu School of Communications and Information Engineering Xi’an University of Posts and Telecommunications Xi’an China

In order to make full use of the color information of the image and improve the accuracy of color image segmentation, this paper proposes an adaptive SLIC-based fuzzy intensity dissimilarity thresholding for color image segmentation, which does not need gray conversion. Firstly, the proposed algorithm adaptively selects the number of super-pixels through the sum of image information and image complexity, and uses SLIC technology to extract image super-pixels; Then, the median value of each channel pixel in each super-pixel block is used as the super-pixel value to calculate the super-pixel intensity information, and the super-pixel intensity histogram is counted; Finally, an intensity dissimilarity function based on IT2FS is constructed to search the optimal threshold. On Berkeley images and Weizmann images, the proposed algorithm is compared with the five related algorithms. The experiments show that the proposed algorithm has achieved good results in terms of visual effects and evaluation indicators, which proves the effectiveness of the algorithm.

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Research on the Role of Computer image Technology in visual Communication Design

Research on the Role of Computer Image Technology in Visual ...

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2021 International conference on communications, Electronic Technology and Computer Engineering, CETCE 2021

作者： Fu, Lin School of Arts and Media Anhui University Anhui China

Computer image came into being at the end of 1980s, and it has experienced more than 30 years of development. image processing technology has been widely used and has become modern applied science. Computer technology is playing an increasingly important role in people's daily life. The use of computer technology is becoming more and more extensive along with the construction and development of information society nowadays. People's daily life and work are inseparable. Computer graphics has also been fully valued, which greatly improves the overall effect and level of visual communication design. Graphic image processing technology is also widely used in today's society, the works designed with it can bring great impact on people's vision. This paper analyzes the meaning of computer graphics and image technology and visual communication design, and on this basis, expounds the significance of computer graphics and image technology on the realization of visual communication design elements, hoping that the results can bring some help to the relevant leading city [1]. © Published under licence by IOP Publishing Ltd.

关键词： Computer graphics

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DesnowFormer: an effective transformer-based image desnowing network

DesnowFormer: an effective transformer-based image desnowing...

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IEEE visual communications and image processing (VCIP)

作者： Ting Zhang Nanfeng Jiang Junhong Lin Jielian Lin Tiesong Zhao Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou University Fuzhou China

ISBN: (纸本)9781665475938

Single image desnowing is an important and challenge task for lots of computer vision applications, such as visual tracking and video surveillance. Although existing deep learning-based methods have achieved promising results, most of them rely on the local deep features and neglect global relationship information between the local regions. Therefore, inevitably leading to over-smooth or detail loss results. To solve this issue, we design a UNet-based end-to-end architecture for image desnowing. Specially, to better characterize global information and preserve image detail, we combine Window-based Self-Attention (WSA) transformer block with Residue Spatial Attention (RSA) to build basic unit of our network. Besides, to protect the structure of the image effectively, we also introduce a Residue Channel (RC) loss to guide high-quality image restoration. Extensive experimental results on both synthetic and real-world datasets demonstrate that the proposed model achieves new state-of-the-art results.

关键词： Training Learning systems visualization Computer vision visual communication Semantics Transformers

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Improving image Paragraph Captioning with Dual Relations

Improving Image Paragraph Captioning with Dual Relations

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2022 IEEE International conference on Multimedia and Expo, ICME 2022

作者： Liu, Yun Shi, Yihui Feng, Fangxiang Li, Ruifan Ma, Zhanyu Wang, Xiaojie School of Artificial Intelligence Beijing University of Posts and Telecommunications China Beijing Academy of Artificial Intelligence Beijing China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

image paragraph captioning aims to generate multiple de-scriptive sentences for an image. However, most previous methods ignore the explicit relations among objects resulting in unsatisfactory performance. In this paper, we propose a novel model (i.e., DualRel) to capture spatial and seman-tic relations among objects. Specifically, the spatial relation embedding is obtained solely from images using a predefined geometry pattern. With the help of captions, the semantic relation embedding is learned in a weakly supervised man-ner. These two relation embeddings are then interacted with regional features of objects through a relation-aware attention interaction. It first obtains a visual context vector using regional features. Then with the visual context vector, we obtain the corresponding spatial and semantic relation-aware vectors using attentions. These three vectors are fused with two gates for language decoding to further generate a para-graph. Experimental results on Stanford benchmark dataset show that DualRel achieves remarkable improvements11Code released at https://***/fuyunll07/DualRel. © 2022 IEEE.

关键词： Vectors

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Optimized MobileNetV2 Based on Model Pruning for image Classification

Optimized MobileNetV2 Based on Model Pruning for Image Class...

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IEEE visual communications and image processing (VCIP)

作者： Peng Xiao Yuliang Pang Hao Feng Yu Hao Center for Image and Information Processing (CIIP) Xi'an University of Posts & Telecommunications Xi'an China

ISBN: (纸本)9781665475938

Due to the large memory requirement and a large amount of computation, traditional deep learning networks cannot run on mobile devices as well as embedded devices. In this paper, we propose a new mobile architecture combining MobileNetV2 and pruning, which further decreases the Flops and number of parameters. The performance of MobileNetV2 has been widely demonstrated, and pruning operation can not only allow further model compression but also prevent overfitting. We have done ablation experiments at CIIP Tire Data for different pruning combinations. In addition, we introduced a global hyperparameter to effectively weigh the accuracy and precision. Experiments show that the accuracy of 98.3 % is maintained under the premise that the model size is only 804.5 KB, showing better performance than the baseline method.

关键词： Performance evaluation Solid modeling image recognition image coding visual communication Tires Pattern recognition

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On the Importance of Temporal Dependencies of Weight Updates in Communication Efficient Federated Learning

On the Importance of Temporal Dependencies of Weight Updates...

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IEEE visual communications and image processing (VCIP)

作者： Homayun Afrabandpey Goutham Rangu Honglei Zhang Francesco Criri Emre Aksu Hamed R. Tavakoli Nokia Technologies Finland

ISBN: (纸本)9781665475938

This paper studies the effect of exploiting temporal dependency of successive weight updates on compressing communications in Federated Learning (FL). For this, we propose residual coding for FL, which utilizes temporal dependencies by communicating compressed residuals of the weight updates whenever they are beneficial to bandwidth. We further consider Temporal Context Adaptation (TCA) which compares co-located elements of consecutive weight updates to select optimal setting for compression of bitstream in DeepCABAC encoder. Following experimental settings of MPEG standard on Neural Network Compression (NNC), we demonstrate that both temporal dependency based technologies reduce communication overhead, where the maximum reduction is obtained using both technologies, simultaneously.

关键词： MPEG standards image coding Federated learning visual communication Neural network compression Bandwidth Artificial neural networks

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Machine Vision-based Tool Location and Wear Monitoring in Micro turning: Optical Setup and image processing Approaches

Machine Vision-based Tool Location and Wear Monitoring in Mi...

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Innovations in communications, Electrical and Computer Engineering (ICICEC), International conference on

作者： Shalupriya M K.P. Indira Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Nanobiomaterials Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376524

In micro turning, tool placement, wear, and breakage are crucial as they affect precision and surface finish. Flank wear is problematic since it impacts dimensional accuracy, and current methods that rely on CNC encoder inputs and radius compensation are insufficient for micro turning due to the small tool sizes involved. Detecting flank wear in micro turning is difficult as the tools are often too small for visual inspection, making monitoring at micron levels a challenge. This research investigates using machine vision to monitor tool position and flank wear in micro turning. The optical system, comprising a 12X super zoom lens and 3MP CMOS image sensor, is assessed alongside three lighting techniques: direct, indirect, and backlighting. Preliminary image analysis, using Gaussian filters and histogram equalization, indicates lighting's importance. Early results, comparing new and worn tools using exclusive operators, are promising, but further image enhancements are necessary for accurate classification and wear detection.

关键词： Optical filters Integrated optics visualization Technological innovation Accuracy Lighting Turning Optical imaging Optical sensors Monitoring

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