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Multi-scale Dilated Convolution Transformer for Single image Deraining 25

Multi-scale Dilated Convolution Transformer for Single Image...

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25th IEEE international workshop on Multimedia Signal processing (MMSP)

作者： Wu, Xianhao JiyangLu Wu, Jindi Li, Yufeng Shenyang Aerosp Univ Coll Elect Informat Engn Shenyang Peoples R China

ISBN: (纸本)9798350338935

Recently, Transformer-based methods have achieved significant improvements over convolutional neural networks (CNNs) in single image deraining, due to the powerful ability of modeling non-local information. In fact, rich local-global information representations are equally important for better satisfying rain removal. In this paper, we propose an effective image deraining method by integrating a CNN model into the Transformer backbone to accelerate network convergence, called Multi-scale Dilated-convolution Transformer (MDT), which fully leverages the learning capabilities of Transformers on non-local features, seamlessly integrating local detail extraction and global structural representation. The fundamental building unit of our framework is the Multi-scale Dilated-convolution Transformer Block (MDTB) with different dilation rates, which consists of the Dilconv Self-Attention (DSA) and the Dilconv Feed-Forward Network (DFN). Specifically, the former processes the contextual information via dilated convolutions and enables the model to emphasize spatially-varying rain distribution features, while the latter integrates the dual-branch information to facilitate the local feature learning for better feature aggregation. Extensive evaluations demonstrate that our model reaches superior performance, significantly improving the image deraining quality.

关键词： Single image deraining Transformers Dilated-convolution

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MULTISCALE GRAPH CONSTRUCTION USING non-local CLUSTER FEATURES 34

MULTISCALE GRAPH CONSTRUCTION USING NON-LOCAL CLUSTER FEATUR...

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34th international workshop on Machine Learning for Signal processing

作者： Kaneko, Reina Kojima, Hayate Yanagiya, Kenta Hara, Junya Higashi, Hiroshi Tanaka, Yuichi Osaka Univ Suita Osaka Japan Tokyo Univ Agr & Technol Tokyo Japan

ISBN: (纸本)9798350372267;9798350372250

This paper presents a multiscale graph construction method using both graph and signal features. Multiscale graph is a hierarchical representation of the graph, where a node at each level indicates a cluster in a finer resolution. To obtain the hierarchical clusters, existing methods often use graph clustering;however, they may ignore signal variations. As a result, these methods could fail to detect the clusters having similar features on nodes. In this paper, we consider graph and node-wise features simultaneously for multiscale clustering of a graph. With given clusters of the graph, the clusters are merged hierarchically in three steps: 1) Feature vectors in the clusters are extracted. 2) Similarities among cluster features are calculated using optimal transport. 3) A variable k-nearest neighbor graph (VkNNG) is constructed and graph spectral clustering is applied to the VkNNG to obtain clusters at a coarser scale. Additionally, the multiscale graph in this paper has non-local characteristics: Nodes with similar features are merged even if they are spatially separated. In experiments on multiscale image and point cloud segmentation, we demonstrate the effectiveness of the proposed method.

关键词： Multiscale graph non-local features optimal transport variable k-nearest neighbor graph construction

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No-reference image Quality Assessment via non-local Dependency Modeling 24

No-reference Image Quality Assessment via Non-local Dependen...

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IEEE 24th international workshop on Multimedia Signal processing (MMSP)

作者： Jia, Shuyue Chen, Baoliang Li, Dingquan Wang, Shiqi City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Peng Cheng Lab Shenzhen Peoples R China

ISBN: (数字)9781665471893

ISBN: (纸本)9781665471893

In this paper, we propose a no-reference image quality assessment method based on non-local features learned by a graph neural network (GNN). The proposed quality assessment framework is rooted in the view that the human visual system perceives image quality with long-dependency constructed among different regions, inspiring us to explore the non-local interactions in quality prediction. Instead of relying on convolutional neural network (CNN) based quality assessment methods that primarily focus on local field features, the GNN aiming for non-local quality perception facilitates modeling such long-dependency. In particular, we first adopt superpixel segmentation for the graph nodes construction. Subsequently, a spatial attention module is proposed to integrate the long- and short-range dependencies among the nodes of the whole image. The learned non-local features are finally combined with the local features extracted by the pre-trained CNN, achieving superior performance to the features utilized individually. Experimental results on intra-dataset and cross-dataset settings verify our proposed method's effectiveness and advanced generalization capability. Source codes are publicly accessible at https://***/SuperBruceJia/NLNet-IQA for scientific reproducible research.

关键词： No-reference image quality assessment human visual system non-local modeling superpixel graph neural network

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Deep Mutations have Little Impact 13

Deep Mutations have Little Impact

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international workshop on Genetic Improvement (GI@ICSE)

作者： Langdon, William B. Clark, David UCL Dept Comp Sci London England

ISBN: (纸本)9798400705731

Using MAGPIE (Machine Automated General Performance Improvement via Evolution of software), we measure the impact of genetic improvement (GI) on a non-deterministic deeply nested PARSEC VIPS parallel computing multi-threaded image processing benchmark written in C. More than 53% of mutants compile and generate identical results to the original program. We find about 10% Failed Disruption Propagation (FDP). Excluding internal errors and asserts, almost all changes deeper than 30 nested functions which are Executed and Infect data or change control are not Propagated to the output, i.e. these deep PIE changes have no external effect. Suggesting (where it relies on testing) automatic software engineering on deeply nested code will be hard.

关键词： Software testing robust software fault masking resilience repair automatic code optimisation failed disruption propagation FDP PIE (propagation infection and execution) fitness landscape information theory genetic programming local search SBSE

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Linear operators for filtering digital images based on two-dimensional local spline of the fifth order 3

Linear operators for filtering digital images based on two-d...

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3rd international Conference on Cyber Hygiene and Conflict Management in Global Information Networks, CH and CMiGIN 2024

作者： Prystavka, Pylyp Cholyshkina, Olha Dyriavko, Oleh National Aviation University Liubomyra Huzara Ave. 1 Kyiv03058 Ukraine Interregional Academy of Personnel Management Frometivska Str. 2 Kyiv03039 Ukraine

The paper explores the development and application of linear operators for filtering digital images, particularly through the use of fifth-order polynomial splines. The authors emphasize the importance of high-quality, high-speed image processing in enhancing cybersecurity systems, which require accurate and real-time data analysis for applications such as military intelligence and UAV navigation. They propose using B-splines, which offer precise approximation capabilities while maintaining computational efficiency. The paper outlines a method for representing these splines in a manner that reduces computational complexity, making them suitable for real-time processing in environments with high data throughput demands. The research highlights the advantages of using wider window filters and linear operators to maintain image accuracy and fidelity. It demonstrates how these techniques can be effectively applied to a range of signal processing tasks beyond image filtering, including audio and telecommunications. The experimental results presented in the paper indicate that the proposed filters significantly improve the detection and accuracy of special points in digital images, which is crucial for UAV navigation and other critical applications. The authors conclude that the use of these advanced filtering techniques can lead to more efficient and sophisticated image processing systems, with potential applications across various fields. In addition to the practical applications, the paper also discusses the theoretical underpinnings of splinebased filters, including the derivation of low- and high-frequency filter masks. The authors propose that these filters can be used to perform both sub-band filtering and multi-scale analysis of digital images, leading to improved data processing and analysis capabilities. The research contributes to the ongoing development of efficient image processing techniques that are essential for modern technology and various real-time appl

关键词： Wiener filtering

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Application of Improved Adaptive Genetic Algorithm in Flexible workshop Scheduling 2

Application of Improved Adaptive Genetic Algorithm in Flexib...

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2nd international Conference on image processing, Computer Vision and Machine Learning, ICICML 2023

作者： Xu, Xiaoping Ezhou University School of Information Engineering Ezhou China

ISBN: (纸本)9798350331417

In the problem of flexible job shop scheduling, conventional genetic algorithms exhibit limited exploration capabilities and are prone to getting stuck in local optima. Consequently, this study aims to enhance the traditional genetic algorithm by adapting it to better address the scheduling problem. To do so, a corresponding mathematical model is established, taking into account the unique characteristics of flexible job shop scheduling problems. Within the genetic operations, adaptive improved crossover and mutation operators are employed, enabling non-linear adjustments based on the fitness values of each individual in the population during the iteration process. Moreover, an elitist retention strategy is implemented to minimize completion time and secure the optimal solution. Through this improved approach, the algorithm's global search ability is enhanced, convergence speed is accelerated, population diversity is increased, and optimal solutions for flexible job shop scheduling problems are obtained more quickly. Finally, the algorithm's efficiency and feasibility are demonstrated by successfully obtaining the optimal solution for the LA01 example in the workshop scheduling problem through testing.. © 2023 IEEE.

关键词： adaptive Flexible job shop scheduling genetic algorithm genetic factor

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locally Adaptive processing of Color Tensor images Represented as Vector Fields

Locally Adaptive Processing of Color Tensor Images Represent...

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international workshop on New Approaches for Multidimensional Signal processing, NAMSP 2023

作者： Jain, Lakhmi C. Kountchev, Roumen K. Kountcheva, Roumiana A. KES International Selby United Kingdom Technical University of Sofia Sofia1000 Bulgaria TK Engineering Sofia1582 Bulgaria

ISBN: (纸本)9789819727438

A new approach for locally-adaptive processing of color RGB images represented as tensors of size M × N × 3, is offered in this work. Unlike the famous similar methods of the kind, the processing here is executed on a single matrix only, which comprises the modules of the vectors, corresponding to the image pixels’ colors. A group of related basic algorithms for locally-adaptive processing is presented, which have lower computational complexity than that of the algorithms, applied individually on each of the RGB components. As it is known, in the famous color RGB transform models of the kind YCrCb, HSV, HSI, Lab, KLT, etc., the processing is applied on the most powerful transformed color component only, and after inverse operation, the original RGB model is restored. In contrast, the idea for locally-adaptive processing does not need direct and inverse transform of the color model. Together with this, the brightness and the color hue of the processed image pixels, are retained. The characteristics of the proposed basic algorithms for contrast enhancement, linear and non-linear sharpness filtration, noise suppression, and texture segmentation, are defined. Some examples for locally-adaptive processing of color medical images are given, which illustrate the related algorithms. The presented approach could be also used for other kinds of color images, where the visibility of their local structure is of high importance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Color

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Particle image velocimetry image processing to assess cell distribution within bioreactors

Particle image velocimetry image processing to assess cell d...

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2022 international workshop in Neurodevelopmental Impairments in Preterm Children - Computational Advancements, DETERMINED 2022

作者： Pistillo, Michele Scamarcio, Margherita Liguori, Federica Mastantuono, Maurizio Gramazio, Simona Ambrico, Alfredo Magarelli, Rosaria Alessandra Martino, Maria Trupo, Mario Merco, Miriam Ledda, Mario D’urso Labate, Giuseppe Falvo Cellex Srl Piazzale delle Belle Arti 2 Rome00196 Italy AKKA Technologies Italy Life Sciences division via Enrico Tazzoli 215/12b Torino10137 Italy Rotondella75026 Italy Via Fosso del Cavaliere 100 Rome00133 Italy

Cell cultures suspended in bioreactors in a fluid environment are the basis for cell expansion and important medical products manufacturing. Assessing local cell distribution within bioreactors may provide information to increase cell production efficiency. Hydrodynamics characterizations of bioreactors are typically performed via Particle image Velocimetry (PIV) with fluorescent polystyrene microspheres or Computational Fluid Dynamics (CFD), while local cell distribution is monitored through expensive sensors or direct sampling. However, PIV and CFD analysis lack of cell behaviour representativity, while direct sampling give average and local information and may impact cell culture conditions. In this study a novel non-invasive method, focusing on the optical investigation of suspended fluorescent nanoparticles (NPs) -labelled Chinese hamster ovary (CHO) cells distribution within SUSPENCE® bioreactor through PIV image processing, is presented. Our investigation showcases the favourable effect of an innovative NPs internalisation approach in terms of cellular uptake efficiency and fluorescence brightness. Moreover, NPs-labelled CHO cells (NP-CHO) PIV image processing and analysis robustness is validated by cell sampling and sample processing. Furthermore, the turbulent kinetic energy distribution to gain insight of the impact of hydrodynamic conditions on cell culture is evaluated. © 2022 Copyright for this paper by its authors.

关键词： Nanoparticles

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Blind image separation for document restoration using plug-and-play approach 23

Blind image separation for document restoration using plug-a...

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23rd IEEE international workshop on Multimedia Signal processing (IEEE MMSP)

作者： Coba, Xhenis Feng, Fangchen Beghdadi, Azeddine Univ Sorbonne Paris Nord Lab Traitement & Transport Informat L2TI Villetaneuse France

ISBN: (纸本)9781665432870

In this paper we propose a new method for document image restoration based on Blind Source Separation. The existing separation methods rely on the general properties of source images such as independence, sparsity, and non-negativity. In this work we show that by exploiting some characteristics of image denoising methods in a play-and-plug scheme, efficient BSS results could be achieved. In particular, we show that the use of BM3D and non-local Means denoising methods as ingredients in the proposed scheme, which exploits the non-local properties of the image, leads to better image separation in terms of convergence rate and perceptual image quality. We also propose to use the dictionary-learning approach to take the concept of visual chirality into consideration. Finally, we apply the proposed scheme to document image restoration problem and show its advantage through experiments and objective performance evaluation.

关键词： Blind image separation Document restoration Plug-and-play image denoising Dictionary learning

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Multi-Scale Dilated Convolution Transformer for Single image Deraining

Multi-Scale Dilated Convolution Transformer for Single Image...

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IEEE workshop on Multimedia Signal processing

作者： Xianhao Wu Jiyang Lu Jindi Wu Yufeng Li College of Electronic Information Engineering Shenyang Aerospace University Shenyang China

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