检索结果-内蒙古大学图书馆

Towards Adversarial Robustness and Reducing Uncertainty Bias through Expert Regularized Pseudo-Bidirectional Alignment in Transductive Zero Shot Learning 27th

Towards Adversarial Robustness and Reducing Uncertainty Bias...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Kumar Sinha, Abhishek Mishra, Deepak Moorthi, S. Manthira Signal and Image Processing Area Space Applications Center Ahmedabad India Indian Institute of Space Science and Technology Thiruvananthapuram India

ISBN: (纸本)9783031781827

Transductive zero-shot learning (TZSL) aims to minimize the domain shift between the learned and true distribution of the unseen classes by allowing access to the unpaired samples from unseen classes. While many distribution alignment based methods attempt to align both visual and semantic spaces to train the classifier, their performance is still limited by confirmation bias. Additionally, bidirectional alignment approaches are based on the strong assumption that the intrinsic dimensions of visual and semantic spaces are the same, which is rarely true. In this work, we first highlight the limitations of bidirectional alignment in terms of intrinsic dimensionality. We then present a pseudo-bidirectional approach that, without any underlying assumptions on these spaces, utilizes the learned visual-to-attribute mapping to minimize the distribution shift between learned and true unseen visual feature distributions. We further utilize an entangled loss between semantic and visual space to minimize the confirmation or uncertainty bias and improve the adversarial robustness. We, theoretically and empirically, show the performance gain in addition to the adversarial robustness under the proposed setting. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Bag-Level Multiple Instance Learning for Acute Stress Detection from Video Data

Bag-Level Multiple Instance Learning for Acute Stress Detect...

引用

18th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2025

作者： Brügge, Nele Sophie Korda, Alexandra Borgwardt, Stefan Andreou, Christina Giannakakis, Giorgos Handels, Heinz German Research Center for Artificial Intelligence AI in Medical Image and Signal Processing Lübeck Germany Translational Psychiatry Department of Psychiatry and Psychotherapy University of Luebeck Lübeck23562 Germany Heraklion Greece Department of Electronic Engineering Hellenic Mediterranean University Chania Greece Institute of Agri-food and Life Sciences University Research and Innovation Center Hellenic Mediterranean University Heraklion Greece Institute of Medical Informatics University of Luebeck Lübeck Germany

Stress detection is a complex challenge with implications for health and well-being. It often relies on sensors recording biomarkers and biosignals, which can be uncomfortable and alter behaviour. Video-based facial feature analysis offers a noninvasive alternative. This study explores video-level stress detection using top-k Multiple Instance Learning applied to medical videos. The approach is motivated by the assumption that subjects partly show normal behaviour while performing stressful experimental tasks. Our contributions include a tailored temporal feature network and optimised data utilisation by additionally incorporating bottom-k snippets. Leave-five-subjects-out stress detection results of 95.46% accuracy and 95.49% F1 score demonstrate the potential of our approach, outperforming the baseline methods. Additionally, through multiple instance learning, it is possible to show which temporal video segments the network pays particular attention to. © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Segmentation of Welding Defects using Level Set Methods

引用

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2012年第6期7卷 1001-1008页

作者： Mohammed, Halimi Naim, Ramou Image and Signal Processing Laboratory. Welding and Control Research Center

Non-destructive testing (NDT) is a technique used in science and industry to evaluate the properties of a material without causing damage. In this paper we propose a method for segmenting radiographic images of welding in order to extract the welding defects which may occur during the welding process. We study different methods of level set and choose the model adapted to our application. The methods presented here take the property of local segmentation geodesic active contours and have the ability to change the topology automatically. The computation time is considerably reduced after taking into account a new level set function which eliminates the re-initialization procedure. Satisfactory results are obtained after applying this algorithm both on synthetic and real images.

关键词： image segmentation Level set Weld defects Radiographic image

来源：评论

学校读者我要写书评

暂无评论

Adaptive lapped transform-based image coding

引用

IEEE signal processing LETTERS 1997年第9期4卷 245-247页

作者： Klausutis, TJ Madisetti, VK Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA USA

A structure is presented for implementing perfectly reconstructing time-varying linear-phase paraunitary filterbanks (LPPUFB) using a novel adaptive lapped transform (ALT), The ALT is based on the generalized lapped orthogonal transform (GenLOT), A time-varying filterbank is constructed through the factorization of the GenLOT into cascaded matrix stages, Variable-length LT's are subsequently generated by cascading a number of these matrix stages to build filters of specific length, An embedded ALT image codec is presented.

关键词： GenLOT image coding lapped transform time-varying filterbank

来源：评论

学校读者我要写书评

暂无评论

A constrained optimization approach to multiuser detection

引用

IEEE TRANSACTIONS ON signal processing 1997年第1期45卷 258-262页

作者： Schodorf, JB Williams, DB Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA USA

A linear multiuser detection scheme based on constrained optimization is presented, Constraints are constructed from knowledge of users' codes and associated timing. Both single- and multiple-constraint detectors are derived and shown to have interesting relationships to existing detectors. Simulation results, presented in the form of bit error rate curves, demonstrate the receiver's performance.

关键词： Constraint optimization Multiuser detection Interference constraints AWGN Detectors Interference cancellation Multiaccess communication Timing Bit error rate Additive white noise

来源：评论

学校读者我要写书评

暂无评论

Analyzing Cognitive Patterns in Gifted Children Using MRI and Morphometric Similarity Networks

Analyzing Cognitive Patterns in Gifted Children Using MRI an...

引用

18th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2025

作者： Han, Shuning Duan, Feng Vilaseca, Gemma Vilaró, Núria Caiafa, Cesar F. Sun, Zhe Solé-Casals, Jordi Data and Signal Processing Research Group University of Vic-Central University of Catalonia Vic Catalonia Spain Image Processing Research Group RIKEN Center for Advanced Photonics RIKEN Saitama Wako-Shi Japan Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China Psychological Department Oms and Prat school Fundació Catalunya- La Pedrera Catalonia Manresa Spain Oms Foundation Catalonia Manresa Spain Instituto Argentino de Radioastronomıa-CCT La Plata CONICET / CIC-PBA / UNLP Argentina Faculty of Health Data Science Juntendo University Chiba Urayasu Japan Department of Psychiatry University of Cambridge Cambridge United Kingdom

Advances in non-invasive neuroimaging, such as structural magnetic resonance imaging (sMRI), have en abled the construction of structural brain networks (SBNs), allowing in vivo mapping of anatomical connec tions. This study investigates brain network structural differences linked to different intelligence levels in children by individual morphometric similarity networks (MSNs) derived from sMRI data. Through group and individual-level analyses, we aim to uncover key topological features associated with cognitive perfor mance and to identify a suitable connection density for SBN analysis. Connection density strongly affects global and nodal topological features, with a range of p = 0.05 to 0.15 recommended for stable and optimal results. Gifted individuals exhibit stronger intra-hemispheric and intra-modular connectivity, a more balanced distribution of left-to-right intra-hemispheric connections, and lower mean versatility, supporting efficient and stable cognitive processing. Moreover, anatomical modularity analyses based on von Economo indicate that higher cognitive performance is linked to enhanced connectivity in specific areas (such as secondary sensory area, motor to association area and secondary sensory to limbic area), alongside selective reduction in cer tain modular connections (such as motor to insular area, association to secondary sensory area and motor to secondary sensory area). Furthermore, topological features, including participation coefficient and local effi ciency, are linked to cognitive performance. These findings provide valuable insights into the SBNs underlying cognitive levels in children. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Brain mapping

来源：评论

学校读者我要写书评

暂无评论

Evaluating Radiomics Feature Reduction for Thyroid Nodule Segmentation in Thermal Imaging 3rd

Evaluating Radiomics Feature Reduction for Thyroid Nodule Se...

引用

3rd International Conference on Artificial Intelligence over Infrared images for Medical Applications, AIIIMA 2024

作者： Etehadtavakol, Mehdi Etehadtavakol, Mahnaz Moallem, Golnaz Ng, Eddie Y. K. Student Research Committee School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran*** Iran Department of Medical Physics School of Medicine Isfahan University of Medical Sciences Isfahan81745-33871 Iran Medical Image and Signal Processing Research Center Isfahan University of Medical Sciences Isfahan81746-73461 Iran Postdoctoral Research Fellow Stanford School of Medicine Palo AltoCA United States School of Mechanical and Aerospace Engineering College of Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

ISBN: (纸本)9783031765834

Radiomics encompasses a variety of image attributes, including intensity, texture, shape, and spatial relationships among pixels. In this study, we applied four feature selection techniques: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Recursive Feature Elimination (RFE), to reduce the dimensionality of radiomic features extracted from thyroid thermal images. Subsequently, we employed three models: U-Net with a VGG16 backbone, U-Net with ResNet50 backbone, and U-Net with DenseNet121 backbone to segment thyroid nodules. The U-Net with a VGG16 backbone combined with the LDA model achieved an average Dice coefficient of 0.4035, significantly outperforming the other models. These results highlight the potential of feature reduction techniques in enhancing thyroid nodule segmentation in thermal imaging. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Feature Reduction Thermal Imaging Thyroid Nodule Segmentation

来源：评论

学校读者我要写书评

暂无评论

On homomorphic deconvolution of bandpass signals

引用

IEEE TRANSACTIONS ON signal processing 1997年第10期45卷 2499-2514页

作者： Marenco, AL Madisetti, VK Center for Signal and Image Processing (CSIP) Georgia Institute of Technology School of Electrical and Computer Engineering Atlanta GA USA

A convolution may be represented as x(.) = r(.)* w(.). The goal of deconvolution is to extract r(.) and w(.) from a knowledge of x(.) and finds numerous applications in digital signal processing, Of practical interest in oil exploration is the case where w(.) is a seismic pressure wavelet, x(.) is the observed seismic response, and, (.) is the reflectivity of the earth, A number of procedures have been proposed, including predictive, deterministic, and homomorphic deconvolution, Homomorphic deconvolution has been found to be particularly efficient for those cases where x(.) is known to be fullband. This paper presents a robust constructive procedure for efficient homomorphic deconvolution for those cases where x(.) is a bandpass signal, Extensive comparisons with other methods for deconvolving bandpass signals on measured seismic data traces (including the Novaya Zemlya event) illustrate the improvement in the deconvolution.

关键词： Deconvolution Convolution Reflection Digital signal processing Reflectivity Seismic measurements signal processing Pollution measurement Cepstral analysis Cepstrum

来源：评论

学校读者我要写书评

暂无评论

An MPEG audio decoder based on 16-bit integer arithmetic and SIMD usage 1

An MPEG audio decoder based on 16-bit integer arithmetic and...

引用

IEEE 1st Workshop on Multimedia signal processing

作者： Hans, M Center for Signal and Image Processing Georgia Institute of Technology United States

ISBN: (纸本)0780337808

We report the design and implementation of a compliant MPEG audio decoder for Layers I and II with new algorithmic and architectural enhancements. The proposed algorithm uses a scaled 32-point Chen DCT and is implemented using 18-bit integer arithmetic. Measurements and results are given for a complete decoder implemented and optimized for Intel's MMX technology.

关键词： Motion Picture Experts Group standards

来源：评论

学校读者我要写书评

暂无评论

Spatio-temporal wavelet transforms for digital signal analysis

引用

signal processing 1997年第1期60卷 23-41页

作者： Leduc, JP Georgia Institute of Technology School of Electrical and Computer Engineering Center of Signal and Image Processing Atlanta GA 30332-0250 USA

The goal of this paper is to investigate spatio-temporal continuous wavelet transforms. A new wavelet family, called the Galilean wavelet, has been designed to tune to four main parameters, namely, scale, spatio-temporal position, spatial orientation, and velocity. The paper starts with the theory of motion-compensated wavelet filtering in the discrete realm of image processing. As a major difference from multi-dimensional homogeneous spaces, spatio-temporal signal involves motion that warps the signal along the trajectories. Modeling motion with 2-D affine transformations leads to spatio-temporal generalizations. Decomposition into elementary operators leads to developing transformation groups and exploiting the related representation theory. The construction of continuous spatio-temporal wavelets in R-n x R spaces is then handled with classical techniques of calculation. Close connections may then be established among all the spatio-temporal wavelet transforms through different sets of transformations. This approach generates a general framework for the study of future tools. Frames of wavelets are thereafter investigated to revisit discrete wavelet transforms in a more general way. Eventually, illustrations demonstrate the ability of Galilean wavelet transforms to analyze spatio-temporal signals. (C) 1997 Elsevier Science B.V.

关键词： wavelet transforms spatio-temporal signals image sequences motion analysis group of transformations regions of interest selective feature extraction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：