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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Shuzhan Xiao, Lei Huang, Hui Hu, Zhongyi Wenzhou University Institute of Intelligent Information System Wenzhou University Key Laboratory of Intelligent Image Processing and Analysis College of Computer Science and Artificial Intelligence Wenzhou China

ISBN: (纸本)9798350386226

The current diagnostic methods for Autism Spectrum Disorder (ASD) based on Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) face two significant challenges. Firstly, the functional connectivity networks (FCNs) of the brain are subject to uncertainty due to noise interference during the rs-fMRI acquisition process. Secondly, variations in equipment parameters across different imaging sites lead to diverse distributions of collected features. To address these issues, this paper introduces a novel Multi-Task Stacked Adaptive Fuzzy Neural Network (AT-STTSK) specifically designed for Autism Spectrum Disorder (ASD) classification. The proposed network seamlessly integrates a Multi-Output TSK (MO-TSK) fuzzy system, a Stacked Autoencoder (SAE), and a Transformer. This integration aims to reduce the impact of uncertainty factors, enhance the model's interpretability, and leverage the multi-head attention mechanisms to capture both local and global information, thus strengthening feature learning. Additionally, we explore the utilization of a Contrastive Learning (CL) strategy to further optimize the model. By incorporating these advancements, our AT-STTSK network offers a promising approach for improving the accuracy and reliability of ASD diagnosis based on rs-fMRI data. The validity of the method in this paper is verified on ABIDE dataset, and the result shows that the accuracy rate can reach 85.7% at most. © 2024 IEEE.

关键词： Diseases

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Controllability of neighborhood Corona product networks

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Science China(information Sciences) 2024年第12期67卷 327-328页

作者： Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology

Controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability has been widely studied and applied to system engineering and control theory, power systems, aerospace, and quantum systems. Various classical criteria include the Gram matrix criterion, Kalman rank criterion, and PBH test.

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Spatial Quality Assessment of Pansharpened images Based on Gray Level Co-Occurrence Matrix 12

Spatial Quality Assessment of Pansharpened Images Based on G...

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12th Iranian/2nd International Conference on Machine Vision and image processing, MVIP 2022

作者： Aghapour Maleki, Shiva Ghassemian, Hassan Tarbiat Modares University Image Processing and Information Analysis Laboratory Faculty of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9781665412162

Assessing the quality of pansharpened images is a critical issue in order to obtain a quantitative score to represent the quality and compare the performance of different fusion methods. Most of the introduced metrics for pansharpened image quality assessment, evaluate the spectral content of the image, while in different applications of remote sensing like detection and identification of image objects, spatial quality has an important role. In the current study, a new index for spatial quality assessment is introduced that extracts gray level co-occurrence matrix (GLCM) from distorted and reference images and compares the similarities of these features. The tempere image database 2013 (TID2013) that provides reference and different types of distorted images with subjective scores of each image is used as the desired database. To solve the high computational complexity of obtaining GLCM features, the fast GLCM method is employed. In this way, 16 different features are extracted. To select the features that have the most consistency with the human visual system (HVS), the forward floating search method is used as a feature selection method and five features are obtained as the final features to form the desired index. Experimental results show the efficiency of the proposed method in determining the spatial quality of fused images compared with that of the available quality assessment metrics. © 2022 IEEE.

关键词： Remote sensing

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Assessment and comparison of image quality between two real-time sequences for dynamic MRI of distal joints at 3.0 Tesla (vol 64 , pg 1093 , 2023 )

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ACTA RADIOLOGICA 2023年第10期64卷 2686-2686页

作者： Garetier, M. Rousset, J. Makki, K. Department of Radiology Military Teaching Hospital Clermont-Tonnerre Brest FranceDepartment of Radiology University Hospital Morvan Brest FranceLaboratory of Medical Information Processing (LATIM) INSERM-UMR 1101 Brest France Department of Radiology Military Teaching Hospital Clermont-Tonnerre Brest France INRIA Fluminance Rennes FranceIFPEN Rueil-Malmaison France Laboratory of Medical Information Processing (LATIM) INSERM-UMR 1101 Brest FranceDepartment of Physical and Medical Rehabilitation University Hospital Morvan Brest FranceDepartment of Paediatric Physical and Medical Rehabilitation Fondation Ildys Brest FranceUniversity of Western Brittany (UBO) Brest France Laboratory of Medical Information Processing (LATIM) INSERM-UMR 1101 Brest FranceIMT Atlantique UBL Brest France Laboratory of Medical Information Processing (LATIM) INSERM-UMR 1101 Brest FranceUniversity of Western Brittany (UBO) Brest FranceDepartment of Radiology University Hospital La Cavale Blanche Brest France Laboratory of Medical Information Processing (LATIM) INSERM-UMR 1101 Brest FranceSymbiosis Centre for Medical Image Analysis Symbiosis International University Pune India

Background Real-time sequences allow functional evaluation of various joint structures during a continuous motion and help understand the pathomechanics of underlying musculoskeletal diseases. Purpose To assess and compare the image quality of the two most frequently used real-time sequences for joint dynamic magnetic resonance imaging (MRI), acquired during finger and ankle joint motion. Material and Methods A real-time dynamic acquisition protocol, including radiofrequency (RF)-spoiled and balanced steady-state free precession (bSSFP) sequences, optimized for temporal resolution with similar spatial resolution, was performed using a 3.0-T MRI scanner on 10 fingers and 12 ankles from healthy individuals during active motion. image quality criteria were evaluated on each time frame and compared between these two sequences. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were determined and compared from regions of interest placed on cortical bone, tendon, fat, and muscle. Visualization of anatomical structures and overall image quality appreciation were rated by two radiologists using a 0–10 grading scale. Results Mean CNR was significantly higher with bSSFP sequence compared to RF-spoiled sequence. The grading score was in the range of 5–9.3 and was significantly higher with RF-spoiled sequence for bone and joint evaluation and overall image appreciation on the two joints. The standard deviation for SNR, CNR, and grading score during motion was smaller with RF-spoiled sequence for both the joints. The inter-reader reliability was excellent (>0.75) for evaluating anatomical structures in both sequences. Conclusion A RF-spoiled real-time sequence is recommended for the in vivo clinical evaluation of distal joints on a 3.0-T MRI scanner.

关键词： Joints magnetic resonance imaging motion musculoskeletal system objective metrics quality

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Infrared Small Moving Target Detection Based on Spatial-Temporal-Frequency analysis

Infrared Small Moving Target Detection Based on Spatial-Temp...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yuhan Liu Aersi Aliha Xiaoyang Wang Yuxin Hu Guangyao Zhou Aerospace Information Research Institute Chinese Academy of Sciences (CAS) Information Processing and Image Analysis Laboratory CAS University of Chinese Academy of Sciences University of Exeter

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

The Infrared Searching and Tracking System (IRSTS) plays an important role in both military and citizen life, contributing to crucial areas such as security surveillance and transportation, and so on. As the core step in the system, methods for infrared moving target detection and tracking attract much attention in recent years, especially for several specific small targets like unmanned aerial vehicles (UAVs). In this work, a spatial-temporal-frequency feature fusion based approach is proposed. Firstly, the infrared sequential images are decomposed via 3D wavelet transform. Only the high frequency information in spatial and temporal domains is reconstructed to form the reconstructed sequence. A background suppression strategy from temporal to spatial domain is secondly applied in the reconstruction images and the target is acquired by adjust segmentation. Experimental results demonstrate that the proposed method achieves competitive performance both in qualitative and quantitative comparisons.

关键词： Wavelet transforms Target tracking Three-dimensional displays Surveillance Transportation Object detection Interference

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A flexible organohydrogel-based humidity sensor for noncontact artificial sensation

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Science China(Technological Sciences) 2022年第1期65卷 191-200页

作者： ZHANG Yu LI Chen YANG Han ZHAO Rui CHEN XinJian NIE BaoQing HU Liang Medical Image Processing Analysis and Visualization(MIPAV)School of Electronic and Information EngineeringSoochow UniversitySuzhou 215000China State Key Laboratory of Radiation Medicine and Protection School for Radiological and Interdisciplinary Sciences(RAD-X)and Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education InstitutionsSoochow UniversitySuzhou 215000China

In this paper,we propose a simple organohydrogel based capacitive humidity sensor for noncontact artificial sensation *** sensor is simple in design and consists of a transparent polyacrylamide organohydrogel thin film attached on a flexible inter-digit electrode *** process of water absorption and desorption is reversible,thus the dielectric of the organohydrogel film as well as the overall capacitance is dependent on environmental *** water absorption capacity and structural reliability of the device have been largely improved by adding glycerol in the organohydrogel *** optimizing both the glycerol concentration and organohydrogel film thickness,the sensor can respond to cyclic humidity changes in a period of 300 *** addition,this sensor achieves a high relative capacitance increase(by 20 folds)in a wide relative humidity range(12%-95%).The sensor also exhibits high stability under different bending curvatures(up to 6.81 mm),wide temperature changes(20℃-40℃)and external pressures(0-8 N).To demonstrate the applications in wearable electronics,we found that the sensor was successful in detecting respiration intensity and rate as well as the difference in moisture content in various objects,i.e.,human skin and leaf *** sensor is highly sensitive and can be useful in the detection of the widerange of humidity changes.

关键词： humidity sensor organohydrogel wearable electronics

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Inspection Method of Track Facilities Using image analysis of images Taken from Front of Trains

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Quarterly Report of RTRI (Railway Technical Research Institute) 2023年第3期64卷 205-210页

作者： Nagamine, Nozomi Goda, Wataru Maeda, Riho Tsubokawa, Yosuke Kato, So Itoi, Kensuke Head of Image Analysis Laboratory Information and Communication Technology Division Research Areas: Computer Vision Image Processing Signalling Systems Japan Image Analysis Laboratory Information and Communication Technology Division Research Areas: Computer Vision Image Processing Japan Head of Track Geometry and Maintenance Laboratory Track Technology Division Research Areas: Track Measuring Japan Track Geometry and Maintenance Laboratory Track Technology Division Research Areas: Track Measuring Japan Research Areas: Track Measuring Japan

Appropriate maintenance of tracks is vital for the safe operation of railways. Properly managing track facilities is necessary to prevent buckling of rails. Changes in society are creating a shortage of workers, a decrease in skilled engineers, a decrease in passenger income, and an increase in the need to develop low-cost inspection methods which do not require experience. Therefore, we have developed a method using only inexpensive camcorders, which can extract information from images to detect joint gaps, wooden sleeper deterioration and ballast shape, and estimate the kilometer point of these images to locate the installations in question. This paper describes the outline of the method and its application results. © 2023 Ken-yusha Inc.. All rights reserved.

关键词： Inspection

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Attention-stacking adaptive fuzzy neural networks for autism diagnosis

Attention-stacking adaptive fuzzy neural networks for autism...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Shuzhan Zhang Lei Xiao Hui Huang Zhongyi Hu College of Computer Science and Artificial Intelligence Wenzhou University Institute of Intelligent Information System Wenzhou University Key Laboratory of Intelligent Image Processing and Analysis Wenzhou China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

关键词： Representation learning Autism Accuracy Uncertainty Attention mechanisms Adaptive systems Noise Contrastive learning Transformers Fuzzy neural networks

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A Survey of Text Detection Algorithms in images Based on Deep Learning 4

A Survey of Text Detection Algorithms in Images Based on Dee...

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4th International Conference on Natural Language processing, ICNLP 2022

作者： Li, Linna Hu, Cuicui Liu, Ying Xi'an University of Posts and Telecommunications Network Public Opinion Monitoring and Analysis Center Shaanxi Xi'an710121 China Xi'an University of Posts and Telecommunications College Key Laboratory of Electronic Information Application Technology for Scene Investigation Ministry of Public Security Center for Image and Information Processing Shaanxi Xi'an710121 China

ISBN: (数字)9781665495448

ISBN: (纸本)9781665495448

Nowadays, text detection has infiltrated various industries like banking, education, criminal investigation, network public opinion, and more. However, the traditional way of text detection is largely dependent on the characteristics of manual design, which is time-consuming, laborious and inaccuracy. With the emergence of deep learning technology, text detection has already been transformed from text detection in static documents to more practical text detection in natural scenes. To address such challenges as complex background, improper acquisition, and multilingual text in natural scene images, there have been various improved neural network structures constructed. Especially, the performance of text detection in various scenes has been significantly improved. In learning in different scenes are summarized in detail. According to the different text objects in detection, the existing methods are classified into two categories as top-down and bottom-up, and the logic structure, advantages and disadvantages of various algorithms are summarized. In addition, the commonly used data sets and performance evaluation indexes are analyzed and explained, the practical application of text detection in different fields is introduced, and the future trend of research and development are indicated. © 2022 IEEE.

关键词： Deep learning

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Topic Embedded Representation Enhanced Variational Wasserstein Autoencoder for Text Modeling 5

Topic Embedded Representation Enhanced Variational Wasserste...

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5th IEEE International Conference on Electronics Technology, ICET 2022

作者： Xiang, Zheng Liu, Xiaoming Yang, Guan Liu, Yang Zhongyuan University of Technology School of Computer Science Zhengzhou China Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China Key Laboratory of text processing and image understanding Zhengzhou China Xidian University State Key Laboratory of Integrated Services Networks Xi'an China Shandong University Key Lab of Cryptologic Technology and Information Security Ministry of Education Xi'an China

ISBN: (纸本)9781665485081

Variational Autoencoder (VAE) is now popular in modeling and language generation tasks, which need to pay attention to the diversity of generation results. The existing models are insufficient in capturing the built-in relationships between topic representation and sequential words. At the same time, there is a massive contradiction between the commonly used simple Gaussian prior and the actual complex distribution of languages. To address the above problems, we introduce a hybrid Wasserstein Autoencoder (WAE) with Topic Embedded Representation (TER) for modeling. TER is obtained through an embedding-based topic model and can capture the dependencies and semantic similarities between topics and words. In this case, the learned latent variable has rich semantic knowledge with the help of TER and is easier to explain and control. Our experiments show that our method is competitive with other VAEs in modeling. © 2022 IEEE.

关键词： Semantics

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