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5th international conference on Neural Computing for Advanced Applications, NCAA 2024

5th International Conference on Neural Computing for Advance...

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5th international conference on Neural Computing for Advanced Applications, NCAA 2024

ISBN: (纸本)9789819770069

the proceedings contain 89 papers. the special focus in this conference is on Neural Computing for Advanced Applications. the topics include: Online Car-Hailing Order Matching Method Based on Demand Clustering and Reinforcement Learning;Multi-objective Optimization of Antenna Based on Improved WOA-BP Neural Network;A Multi-mechanism Collaborative Seagull Optimization Algorithm for Optimizing BP Neural Network Classification Model;an analysis on Balance Model of Exploration and Exploitation Under Decoupled-Learning pattern for Large-Scale Particle Swarm Optimizers;marine Ship Detection Under Fog Conditions Based on an Improved Deep-Learning Approach;skeleton-Based Point Cloud Sampling and Its Facilitation to Classification;multi-agent Reinforcement Learning for Taxi-Fleet Cruising Strategy in Ride-Hailing Services;a New Indoor Occupancy Detection Model by Integrating the Efficient Multi-scale Attention Mechanism into the EfficientDet Model;a Novel Automatic Generation Method for Neural Network by Using Iterative Function System;a Predictive Maintenance Platform for a Conveyor Motor Sensor System Using Recurrent Neural Networks;A Deep Learning-Based Method Facilitates scRNA-seq Cell Type Identification;adaptive Hierarchical Clustering Based Student Group Exercise Recommendation via Multi-objective Evolutionary Method;Quantile Regression and GCN Ensembled Hybrid Interval Forecasting Model for Wind Power Generation;efficient Path Planning for Large-Scale Vehicular Networks via Multi-agent Mean Field Reinforcement Learning;a Fast and Accurate Reconstruction Method for Boiler Temperature Field Based on Inverse Distance Weight and Long Short-Term Memory;RoBERTa-wwm-CBA: A Mental Disease Identification Model Based on RoBERTa-wwm and Hybrid Neural Networks;3D Pose Estimation of Markerless Fish on Deep Learning;safety Helmet-Wearing Detection Method Fusing Pose Estimation;Clothes Image Retrieval via Learnable FashionCLIP;mannequin2Real+: A Two-Stage Framework for Generating P

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5th international conference on Neural Computing for Advanced Applications, NCAA 2024

5th International Conference on Neural Computing for Advance...

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5th international conference on Neural Computing for Advanced Applications, NCAA 2024

ISBN: (纸本)9789819770007

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Signal Processing and Connectivity analysis in Calcium Imaging Data: Unveiling Neuronal Network Dynamics 25

Signal Processing and Connectivity Analysis in Calcium Imagi...

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Proceedings of the 2025 5th international conference on Bioinformatics and Intelligent Computing

作者： Yuanhang Jia Ruinan Yang Institute of Architecture Tianjin University Tianjin Tianjin China Institute of Biomedical Engineering Sichuan University Chengdu Sichuan China

ISBN: (纸本)9798400712203

Calcium imaging, as a means of high temporal and spatial resolution, has been widely used in neuroscience research to monitor the dynamic activity of neuronal networks. In this paper, a comprehensive analysis process for calcium imaging data is proposed to improve the accuracy and effectiveness of data processing, and the analysis is performed using OASIS. First, Z-score standardization is applied to normalize the signal of each neuron to eliminate the difference in signal amplitude between different neurons. then, we design and implement a high-pass filtering method based on the frequency domain to extract high-frequency components and remove low-frequency noise and background signals by fast Fourier transform (FFT), thus enhancing the signal features of neuronal activity. the method was verified on two sets of calcium imaging data, and the results show that the signal after filtering is clearer and can capture the instantaneous activity and synchronization pattern of neurons more effectively. Finally, the result displays that the highly connected neurons in the primary visual cortex mainly interact with a specific population of neurons, indicating the existence of a specific local network structure. this study provides an effective tool for calcium imaging data analysis in the field of neuroscience and is expected to be widely used in the dynamic study of complex neural networks.

关键词： Calcium imaging

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analysis of Driver Attention to Objects While Driving 28th

Analysis of Driver Attention to Objects While Driving

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28th international conference on Image Processing, Computer Vision, and pattern recognition, IPCV 2024, and 23rd international conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

作者： Sarson, Kolby Bauer, Michael Department of Computer Science The University of Western Ontario LondonONN6A5B7 Canada

ISBN: (纸本)9783031859328

A driver’s gaze has often been used to estimate driver attentiveness or focus during driving. these works often rely on simple definitions of what it means to "see", namely, a driver’s gaze falling on an object for a single frame. In this work, we consider a definition of "seen" which requires an object to be gazed upon for a set length of time, or frames, before it can be considered as seen by the driver. this is done by examining consecutive frames to find those where the driver’s gaze remains uninterrupted within a bounding box of a given tracked object over a series of frames. Reliance on multiple frames allows enough time for a driver to process the object gazed upon. We analyze driver gaze on traffic-related objects identified in frames from actual driving sequences. We then consider the impact of different lengths of frame sequences and the size of bounding box overlap across frames on which objects can be taken as "seen" by the driver. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Object detection

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Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting

Longitudinal Segmentation of MS Lesions via Temporal Diffe...

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Workshop on Longitudinal Disease Tracking and Modeling with Medical Images and Data, LDTM 2024, 5th international Workshop on Multiscale Multimodal Medical Imaging, MMMI 2024, 1st Workshop on Machine Learning for Multimodal/-sensor Healthcare Data, ML4MHD2024 and Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support, ML-CDS 2024 held in conjunction with the 27th international conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024

作者： Rokuss, Maximilian R. Kirchhoff, Yannick Roy, Saikat Kovacs, Balint Ulrich, Constantin Wald, Tassilo Zenk, Maximilian Denner, Stefan Isensee, Fabian Vollmuth, Philipp Kleesiek, Jens Maier-Hein, Klaus Division of Medical Image Computing Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Medical Faculty Heidelberg Heidelberg University Heidelberg Germany Helmholtz Imaging German Cancer Research Center Heidelberg Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Neuroimaging Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany University Hospital Essen Essen Germany University Hospital Essen West German Cancer Center Essen Essen Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany

ISBN: (纸本)9783031845246

Accurate segmentation of Multiple Sclerosis (MS) lesions in longitudinal MRI scans is crucial for monitoring disease progression and treatment efficacy. Although changes across time are taken into account when assessing images in clinical practice, most existing deep learning methods treat scans from different timepoints separately. Among studies utilizing longitudinal images, a simple channel-wise concatenation is the primary albeit suboptimal method employed to integrate timepoints. We introduce a novel approach that explicitly incorporates temporal differences between baseline and follow-up scans through a unique architectural inductive bias called Difference Weighting Block. It merges features from two timepoints, emphasizing changes between scans. We achieve superior scores in lesion segmentation (Dice Score, Hausdorff distance) as well as lesion detection (lesion-level F1 score) as compared to state-of-the-art longitudinal and single timepoint models across two datasets. Our code is made publicly available at: ***/MIC-DKFZ/Longitudinal-Difference-Weighting. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image segmentation

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Evaluating the Effectiveness of Large Language Models in Automated Unit Test Generation

Evaluating the Effectiveness of Large Language Models in Aut...

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Advanced Research in Computing (ICARC), international conference on

作者： tharindu Godage Sivaraj Nimishan Shanmuganathan Vasanthapriyan Vigneshwaran Palanisamy Charles Joseph Selvarajah thuseethan Sabaragamuwa University of Sri Lanka Sri Lanka University of Peradeniya Sri Lanka Charles Darwin University Australia University of Southern Queensland Australia

ISBN: (数字)9798331530983

ISBN: (纸本)9798331530990

the increasing use of Artificial Intelligence (AI) in software development underscores the need to select suitable Large Language Models (LLMs) for automating software unit test generation. No prior work has been conducted to evaluate the performance of LLM in this domain. To address this gap, this study evaluates the effectiveness of four prominent LLMs—GPT-4, Claude 3.5, Command-R-08-2024 and Llama 3.1—in generating unit test cases. this study particularly aims to evaluate the performance of these models in real-world testing scenarios. Hence, 106 test cases from 23 test suites based on interviews with software experts and QA engineers are used to ensure relevance and comprehensiveness. these test cases are analyzed using JavaScript Engines Specification Tester (JEST) for code coverage and Stryker for mutation testing while adopting both quantitative and qualitative analysis. the findings reveal that Claude 3.5 consistently outperforms the other models against test success rate, statement coverage, and mutation score with the achieved accuracy of 93.33%, 98.01%, and 89.23% respectively. the results also provide insights into the capabilities of LLMs for automated unit test generation and their integration into the continuous software integration pipeline. Further, the findings authenticated the importance of systematically comparing LLMs for test case generation.

关键词： Measurement Accuracy Large language models Pipelines Software Test pattern generators Standards Optimization Testing Software development management

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On wavelet estimation in semiparametric regression models under convergence system error sequences

On wavelet estimation in semiparametric regression models un...

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5th international conference on wavelet analysis and pattern recognition

作者： Li, Qiang Wu, Yi Natl Univ Def Technol Changsha 410073 Peoples R China

wavelet methods were applied to semiparametric regression models. Weak dependence and moment restrictions on the errors were assumed. the estimators of parameter and nonparameter were presented. the strong consistency... 详细信息

ISBN: (纸本)9781424410651

关键词： wavelet estimation semiparametric regression model convergence system strong consistency

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the properties of biorthogonal bivariate wavelet packets

The properties of biorthogonal bivariate wavelet packets

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5th international conference on wavelet analysis and pattern recognition

作者： Shen, Jian-Guo Yuan, De-You Nanyang Inst Technol Coll Educ Nanyang 473000 Peoples R China

In this paper the notion of univariate orthogonal wavelet packets is generalized. First, the definition nonseparable biorthogonal bivariate wavelet packets is given and a procedure for constructing them is presented N... 详细信息

ISBN: (纸本)9781424410651

关键词： refinement equation multiresolution analysis biorthogonal scaling function biorthogonal wavelet packets

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the new concept and method of wavelet analysis based on differential operator spline

The new concept and method of wavelet analysis based on diff...

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5th international conference on wavelet analysis and pattern recognition

作者： Chen, Yu-Min Qu, Yan-Bin Shen, Yi Harbin Inst Technol WeiHai 264209 Shan Dong Peoples R China

In this paper, the author gives a new concept about wavelet analysis {omega(j), g}, j is an element of z and a concrete method of construction. this method avoids multi-scale analysis but directly define wavelet analy... 详细信息

ISBN: (纸本)9781424410651

关键词： wavelet of differential operator spline multi-scale analysis wavelet analysis generalized differential equation

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the canonical frame of a wavelet frame generated by two functions

The canonical frame of a wavelet frame generated by two func...

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5th international conference on wavelet analysis and pattern recognition

作者： Luo, Ping Guo, Ming-Pu Henan Vocat & Tech Coll Ind Elementary Dept Nanyang 473009 Peoples R China

In this paper, we show that there exist wavelet frame generated by two functions which have good dual wavelet frames, but for which the canonical dual wavelet frame does not consist of wavelets. that is to say, the ca... 详细信息

ISBN: (纸本)9781424410651

关键词： frame operator wavelet frame the canonical wavelet frame dual wavelet frame

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