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检索条件"任意字段=2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021"

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An Algorithm for Skew Angle Estimation and It’s Application Domain

An Algorithm for Skew Angle Estimation and It’s Application...

引用

international conference on signal and Data processing, ICSDP 2019

作者： Kulkarni, Unnati Raju Ghuge, Hemant Goraksh Kulkarni, Revati Anand Thakur, Kirti Vasant Department of Electronics and Telecommunication Engineering Government College of Engineering and Research Avasari Khurd Pune Maharashtra India

ISBN: (纸本)9789811583902

Angle detection and estimation is important in various fields like line following mobile robots, document analysis, construction sites etc. There are several methods and algorithms proposed earlier to do that. This paper represents a new algorithm to estimate skew angle and its possible applications in different fields. In this algorithm, angle in the preprocessed black-white image is estimated using matrix traversal and slope equation from Euclidean geometry. This algorithm can measure the angle between −90 ∘ and +90 ∘ efficiently. © 2021, Springer Nature Singapore Pte Ltd.

关键词： image processing

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Dual-Channel Deep Convolutional Neural Network for Limited-Angle CT image Restoration 9

Dual-Channel Deep Convolutional Neural Network for Limited-A...

引用

9th international conference on Communication, image and signal processing, CCISP 2024

作者： Chen, Yu Zhang, LingLi School of Mathematics and Statistics Chongqing Jiaotong University Chongqing400074 China Chongqing University of Arts and Sciences Chongqing Key Laboratory of Statistical Optimization and Complex Data Chongqing402160 China Chongqing University of Arts and Sciences Chongqing Key Laboratory of Group & Graph Theories and Applications Chongqing402160 China

ISBN: (纸本)9798350356656

Based on the excellent performance of computed tomography (CT) in visualizing the inside of objects, it has become one of the indispensable technologies in the fields of medical diagnosis and industrial inspection. However, due to uncontrollable factors such as radiation dose and detection environment, it is necessary to consider how to obtain projection information within a certain scanning rotation angle range in most cases. In these situations, the reconstructed images using traditional analytical algorithms and iterative algorithms will suffer from limited-angle artifacts. Recently, deep learning technology has gained great attention in the field of image restoration due to its powerful learning ability and its rapid development and application. In order to make up for the limitations of traditional methods in suppressing artifacts in limited-angle CT reconstruction, this paper designs a dual-channel deep convolutional network to remove artifacts in reconstructed images with preserving the details and edges. Simulated and real experiments demonstrate that the presented network can effectively restore images, compared with the classical network. © 2024 IEEE.

关键词： Computerized tomography

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Residual attention fusion network for single image super-resolution 2

Residual attention fusion network for single image super-res...

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2021 2nd international conference on signal processing and Computer Science, SPCS 2021

作者： Zhang, Hao Lan, Chuwen Gao, Zehua School of Information and Communication Engineering Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China

Recently, a very deep convolutional neural network (CNN) demonstrated influential performance in the field of single image super-resolution (SISR). However, most of the CNN-based methods focus on designing deeper and wider network structures alone and do not use the hierarchical and global features in the input image. Therefore, we proposed a residual attention fusion network (RAFN), which is an improved residual fusion (RF) framework, to effectively extract hierarchical features for use in single-image super-resolution. The proposed framework comprises two residual fusion structures composed of several residual and fusion modules, and a continuous memory mechanism is realized by adding a long and short jump connection. The network focuses on learning more effective features. Furthermore, to maximize the power of the RF framework, we introduced global context attention (GCA) module that can model the global context and capture long-distance dependencies. The final RAFN was constructed by applying the proposed RF framework to the GCA blocks. Extensive experiments showed that the proposed network achieved improved performance in the SISR method with fewer parameters, as compared to the methods proposed in previous studies. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Deep neural networks

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End-to-end Multi-source image Phase Retrieval 3

End-to-end Multi-source Image Phase Retrieval

引用

3rd IEEE international conference on Computer Systems, ICCS 2023

作者： Zhao, Nan Song, Tianyang Guo, Yina Taiyuan University of Science and Technology Shanxi China

ISBN: (纸本)9798350313666

The phase information of multi-source hybrid images is prone to confusion during image propagation. Since traditional phase retrieval algorithms require a large number of assumptions that cannot be executed by obtaining amplitude, which makes phase retrieval of multi-source mixed images with phase distortion challenging. To address these phase retrieval problems, inspired by dual learning, we propose an end-to-end phase retrieval algorithm based on Multi-source image Phase Retrieval via dual Generative Adversarial Networks (MPRDGAN). By introducing the Least Square Error in the loss function of the network, the algorithm improves the performance of the model to prevent overfitting and ensures the phase retrieval of multi-source mixed images. Experimental results show that the MPRDGAN algorithm reduces the image restoration error, so that the correlation of restored images can reach more than 94.5%, which is widely used in various images such as face and remote sensing. © 2023 IEEE.

关键词： Generative adversarial networks

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image Fusion for Improving Thermal Human Face image Recognition 5th

Image Fusion for Improving Thermal Human Face Image Recognit...

引用

5th international conference on Cognitive Systems and signal processing, ICCSIP 2020

作者： Wang, Chu Li, Xiaoqiang Wang, Wenfeng Dongbei University of Finance and Economics Dalian China Fudan University Shanghai China Sino-Indian Joint research center of artificial intelligence and robotics Interscience IIMT Bhubaneswar752054 India

ISBN: (纸本)9789811623356

image fusion is widely used in many fields, such as medical research and remote sensing nowadays. To better address thermal human face image recognition problem in surveillance field, extensive research is done using advanced fusion techniques such as Gabor Filtering and Genetic Algorithm. While traditional fusion techniques are often neglected in most cases. For efficient industrial usage, we compared the recognition rates of six conventional image fusion techniques using the benchmark Tufts Face Databases as data source and using recent iteratively reweighted regularized robust coding (IR3C) algorithm as evaluation method. Final results showed a great improvement in thermal image recognition rates even compared with advanced methods. Especially the Weighted Average technique and Principal Component Analysis (PCA) shows 99.488% and 98.721% recognition accuracy with a stable performance in relatively small-scale dataset. Discrete Wavelet Transform (DWT), Pyramid Fusion and Select Maximum technique also maintained over 93% recognition rates. Discussions of those high-performance fusion techniques for particular conditions in surveillance field and certain limitations of our work are proposed. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Discrete wavelet transforms

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Classification model of optical character recognition failures in unrecovered slider serial numbers in hard disk drive manufacturing and image capture processes 13

Classification model of optical character recognition failur...

引用

13th international conference on signal processing Systems, ICSPS 2021

作者： Chousangsuntorn, Chousak Tongloy, Teerawat Chuwongin, Santhad Boonsang, Siridech Department of Electrical Engineering School of Engineering Faculty of Engineering King Mongkut's Institute of Technology Ladkrabang 10270 Thailand College of Advanced Manufacturing Innovation King Mongkut's Institute of Technology Ladkrabang 10270 Thailand

ISBN: (数字)9781510653184

ISBN: (纸本)9781510653177

In hard disk drive (HDD) manufacturing processes, there are unrecovered serial number images about 0.01% from the standard optical character recognition (OCR) reading and deep learning approach. We found several failures from two main causes, i.e. manufacturing process and image capture process during standard OCR reading. We proposed classification model used for recognizing the serial number reading failures based on object detection You-Only-Look- Once (YOLO) algorithm and EfficientNet-B0 classification network as well as histogram analysis. The 1000 images captured by digital camera were used for training (600 images) and validation (400 images) the ROI detection model. The other 2100 captured images were used for training and testing classification OCR failure from manufacturing process model. The model testing was performed in 900 images contained 9 causes (classes) of failures. The proposed model reaches F1 score = 0.94. © COPYRIGHT SPIE.

关键词： Object detection

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4th EAI international conference on advanced Hybrid Information processing, ADHIP 2020

4th EAI International Conference on Advanced Hybrid Informat...

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4th EAI international conference on advanced Hybrid Information processing, ADHIP 2020

ISBN: (纸本)9783030678739

The proceedings contain 43 papers. The special focus in this conference is on advanced Hybrid Information processing. The topics include: Network Dynamic Bad Information Security Filtering algorithms Based on Large Data Analysis;analysis of Intelligent Monitoring Model of Network Security Situation Based on Grid Power Flow;online Monitoring Method for Hazard Source of Power System Network Based on Mobile Internet;an Algorithm of Intelligent Classification For Rotating Mechanical Failure Based on Optimized Support Vector Machine;research on Anti-point Source Jamming Method of Airborne Radar Based on Artificial Intelligence;statistical Analysis of Catalytic Removal of Soot Particles Based on Big Data;research on Electric Drive Control Method Based on Parallel Computing;community Discovery Algorithm Based on Parallel Recommendation in Cloud Computing;Deployment Optimization of Perception Layer Nodes in the Internet of Things Based on NB-IoT Technology;research on Intelligent Investment Prediction Model of Building Based on Support Vector Machine;analysis of Energy Saving Method for Multiple Relay Nodes in Wireless Volume Domain Network;study on Probability Statistics of Unbalanced Cloud Load Scheduling;intelligent Authentication Method for Trusted Access of Mobile Nodes in Internet of Things Driven by Cloud Trust;Research on Dynamic Integration of Multi-objective Data in UI Color Interface;the Application of Visualization of Internet of Things in Online Teaching of Mobile Interactive Interface Optimization;Research on Feature Extraction Method of UAV Video image Based on Target Tracking;automatic Recognition of Tea Bud image Based on Support Vector Machine;automatic Color image Segmentation Based on Visual Characteristics in Cloud Computing.

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4th EAI international conference on advanced Hybrid Information processing, ADHIP 2020

4th EAI International Conference on Advanced Hybrid Informat...

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4th EAI international conference on advanced Hybrid Information processing, ADHIP 2020

ISBN: (纸本)9783030678708

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international conference on signal and Data processing, ICSDP 2019

International Conference on Signal and Data Processing, ICSD...

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international conference on signal and Data processing, ICSDP 2019

ISBN: (纸本)9789811583902

The proceedings contain 48 papers. The special focus in this conference is on signal and Data processing. The topics include: Analysis of Accuracy of Supervised Machine Learning algorithms in Detecting Denial of Service Attacks;An Improved Carrier Frequency Offset Estimation Under Narrowband Interference in OFDM Cognitive Radio;shot Boundary Detection Using Artificial Neural Network;digital image Watermarking by Fusion of Wavelet and Curvelet Transform;machine Learning Feature Selection in Archery Performance;skin Lesion Classification Using Deep Learning;vehicle-to-Vehicle Driver Safety-Related Data Transmission and Reception Using Li-Fi Technology;A Novel Approach for CBIR Using Four-Layered Learning;design of a Power Efficient Multiband Patch Antenna;brain Activity Analysis for Stress Recognition;deep Learning-Based Paperless Attendance Monitoring System;image Analytics to Detect Cigarette in an image Using Deep Learning;custard Apple Leaf Parameter Analysis, Leaf Diseases, and Nutritional Deficiencies Detection Using Machine Learning;Discontinuous PWM Techniques to Eliminate Over-Charging Effects in Four-Level Five-Phase Induction Machine Drives;state of Charge Estimation Using Extended Kalman Filter;Frequency and Pattern Reconfigurable Antenna for WLAN and WiMAX Application;Implementation and Analysis of Low Power Consumption Full Swing GDI Full Adders;preface;deep Semantic Segmentation for Self-driving Cars;single image Rain Removal Using Convolutional Neural Network;ring Oscillator-Based Physical Unclonable Functions;a Robust Approach of Estimating Voice Disorder Due to Thyroid Disease;smart Glasses: Digital Assistance in Industry;implementation of Hand Gesture Recognition System to Aid Deaf-Dumb People;Robust Underwater Animal Detection Adopting CNN with LSTM;face Recognition Using Golden Ratio for Door Access Control System.

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Fully-Online Always-Adaptation of Transfer Functions and Its Application to Sound Source Localization and Separation

Fully-Online Always-Adaptation of Transfer Functions and Its...

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IEEE/RSJ international conference on Intelligent Robots and Systems (IROS)

作者： Nakadai, Kazuhiro Takigahira, Masayuki Kawai, Yusuke Nakajima, Hirofumi Honda Res Inst Japan Co Ltd 8-1 Honcho Wako Saitama 3510188 Japan Tokyo Inst Technol Sch Engn Tokyo Japan Kogakuin Univ Dept Comp Sci Tokyo Japan

ISBN: (纸本)9781665417143

This paper addresses fully-online always-adaptation of a transfer function for robot audition systems based on microphone array processing. The transfer function represents signal propagation characteristics between a microphone and a sound source, which provides essential information for real-world scene analysis, such as sound source localization and separation for robots. Although it is commonly defined as a stationary function, it should be considered together with room acoustics and their environmental changes for practical use, that is, it should be defined as a dynamically-changing function. To fulfill this requirement, we propose a fully-online always-adaptation method for a transfer function, by continuously estimating the transfer function from the observed signals in a passive manner, while performing sound source localization and separation. The proposed method was implemented on open source robot audition software HARK as modules which works online. These modules are applied to sound source localization and separation which are primary functions in robot audition. Experimental results showed that the proposed method successfully adapted to an office environment and improved the performance of sound source localization and separation at a close level to the transfer function recorded in the room.

关键词： Location awareness Measurement image analysis Software algorithms Transfer functions Acoustics Microphone arrays

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