检索结果-内蒙古大学图书馆

Identity and Modality Attributes Driven Multimodal Fusion Networks for Emotion Recognition in Conversations

IEEE Transactions on Multimedia 2025年

作者： Shi, Wuzhen Chen, Xuping Yao, Biyun Wen, Yang Sheng, Bin Shenzhen University Guangdong Province Engineering Laboratory for Digital Creative Technology Guangdong Provincial Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen518060 China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China

Emotion recognition in conversations (ERC) is a crucial aspect of human-computer interaction and plays an important role in various domains, including healthcare, entertainment, and education. Since the conversation data in the form of multimodal sequences is well suited to be constructed into graphs, the methods based on graph convolutional network (GCN) show incomparable advantages. However, existing methods attempt to model the highly uncertain emotional relationships between different speakers, which is not an easy task and may even introduce interference information. Therefore, we propose an identity and modality attributes driven multimodality fusion network (dubbed IMDNet) for emotion recognition in conversations. Specifically, we construct a speaker-centric graph that only connects nodes of the same speaker within modalities to each other, reducing the interference between the emotions of different speakers. We also introduce the attribute embedding mechanism, which facilitates the correct calculation of correlations between nodes for better multimodal feature fusion. Considering that the emotional correlation between utterances will decrease over time, we present an utterance distance attention to make the fusion network pay more attention to the adjacent utterances. Furthermore, we explore the solution to the data imbalance problem suitable for conversation scenarios. Given the presence of possible anomalous samples in the dataset, we opt for the BoundaryFocalLoss. Experiments on the IEMOCAP and MELD datasets show that our IMDNet outperforms the state-of-the-art methods. © 1999-2012 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Distributed intelligent Reflecting Surfaces-Aided Device-to-Device Communications System

引用

Journal of Communications and information Networks 2021年第3期6卷 197-207页

作者： Chiya Zhang Wenyu Chen Qian Chen Chunlong He School of Electronic and Information Engineering Harbin Institute of TechnologyShenzhen 518055China Peng Cheng Laboratory(PCL) Shenzhen 5180523China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen UniversityShenzhen 518060China National Mobile Communications Research Laboratory Southeast UniversityNanjing 211189China

intelligent reflecting surface(IRS)is a revolutionizing and promising technology to improve the high transmission rate of the wireless communication ***,an IRS consists of a great amount of low-cost passive reflecting elements,which reflect the incident signals to the desired user by collaboratively using passive *** paper introduces IRSs into a device-to-device(D2D)underlying cellular system to enhance transmission rate performance of the D2D *** formulate an optimization problem of maximizing the transmission rate of the D2D pairs while satisfying the minimum required rate of the cellular *** address this problem by jointly optimizing the reuse indicator,received beamforming,power allocation,and phase shift *** coordinate descent(BCD)algorithm is adopted to decouple the original problem into four *** form solutions are obtained by solving the sub-problems of optimizing the received beamforming and power ***,Kuhn-Munkres(KM)algorithm and minimization-majorization(MM)algorithm are adopted to solve the sub-problems of optimizing the reuse indicator and phase shift matrices,*** results demonstrate that IRSs can effectively improve the transmission rate of the D2D pairs and our proposed distributed IRSs scheme outperforms the other benchmark schemes.

关键词： intelligent reflecting surface device-to-device communications block coordinate descent

来源：评论

学校读者我要写书评

暂无评论

CMA: A Chromaticity Map Adapter for Robust Detection of Screen-Recapture Document Images

CMA: A Chromaticity Map Adapter for Robust Detection of Scre...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Changsheng Chen Liangwei Lin Yongqi Chen Bin Li Jishen Zeng Jiwu Huang Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security Shenzhen University Alibaba Group Guangdong Laboratory of Machine Perception and Intelligent Computing Faculty of Engineering Shenzhen MSU-BIT University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

The rebroadcasting of screen-recaptured document images introduces a significant risk to the confidential docu-ments processed in government departments and commer-cial companies. However, detecting recaptured document images subjected to distortions from online social networks (OSNs) is challenging since the common forensics cues, such as moiré pattern, are weakened during transmission. In this work, we first devise a pixel-level distortion model of the screen-recaptured document image to identify the robust features of color artifacts. Then, we extract a chromaticity map from the recaptured image to highlight the presence of color artifacts even under low-quality samples. Based on the prior understanding, we design a chromaticity map adapter (CMA) to efficiently extract the chromaticity map, and feed it into the transformer backbone as multi-modal prompt tokens. To evaluate the performance of the pro-posed method, we collect a recaptured office document im-age dataset with over 10K diverse samples. Experimental results demonstrate that the proposed CMA method outper-forms a SOTA approach (with RGB modality only), reducing the average EER from 26.82% to 16.78%. Robustness eval-uation shows that our method achieves 0.8688 and 0.7554 AUCs under samples with JPEG compression $(QF=70)$ and resolution as low as $534\times 503$ pixels.

关键词： Image color analysis Social networking (online) Forensics Splicing Transform coding Feature extraction Distortion

来源：评论

学校读者我要写书评

暂无评论

Image Copy-Move Forgery Detection via Deep Cross-Scale PatchMatch

Image Copy-Move Forgery Detection via Deep Cross-Scale Patch...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Yingjie He Yuanman Li Changsheng Chen Xia Li Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University China

The recently developed deep algorithms achieve promising progress in the field of image copy-move forgery detection (CMFD). However, they have limited generalizability in some practical scenarios, where the copy-move objects may not appear in the training images or cloned regions are from the background. To address the above issues, in this work, we propose a novel end-to-end CMFD framework by integrating merits from both conventional and deep methods. Specifically, we design a deep cross-scale patchmatch method tailored for CMFD to localize copy-move regions. In contrast to existing deep models, our scheme aims to seek explicit and reliable point-to-point matching between source and target regions using features extracted from high-resolution scales. Further, we develop a manipulation region location branch for source/target separation. The proposed CMFD framework is completely differentiable and can be trained in an end-to-end manner. Extensive experimental results demonstrate the high generalizability of our method to different copy-move contents, and the proposed scheme achieves significantly better performance than existing approaches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Contrastive Subspace Clustering with Dissimilarity Regularization

Contrastive Subspace Clustering with Dissimilarity Regulariz...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Jie Chen Wen-Hui Wu Le Ou-Yang College of Electronics and Information Engineering Shenzhen University Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

Subspace Clustering (SC) aims at clustering the data according to its underlying subspaces. However, existing subspace clustering methods fail to make full use of available information. Inspired by advances that contrastive learning has achieved in unsupervised representation learning, we propose a method, namely contrastive subspace clustering with dissimilarity regularization (CSCDR), incorporating contrastive learning into subspace clustering. Specifically, we first construct another view of data through augmentation. Then, the deep subspace clustering networks (DSC-Nets) are used to learn the self-expressive coefficients of data and its augmentation, which further interact with each other by contrastive learning. Moreover, a dissimilarity matrix is formulated based on the latent feature of data to further calibrate the noisy connections in the self-expressive coefficient. And we also utilize the relevant similarity matrix contributing to the multi-positive contrasitve learning, which ameliorates the cluster-collapse problem of representation. Experimental results on several data sets demonstrate the efficacy of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

STROKE LESION SEGMENTATION BASED ON MULTI-RESOLUTION MULTI-DIMENSIONAL AND TWO-STAGE ENSEMBLE LEARNING

STROKE LESION SEGMENTATION BASED ON MULTI-RESOLUTION MULTI-D...

引用

第十六届国际体视学与图像分析学术会议

作者： Li KANG Shunbin LI Jianjun HUANG Jin CHEN College of Electronics and Information Engineering Shenzhen University China and the Guangdong Key Laboratory of Intelligent Information Processing

Stroke is an acute cerebrovascular disease with a extremely high rate of disability and *** early diagnosis is key to developing a treatment plan,early diagnosis of stroke remains difficult due to the challenge of accurately segmenting the *** this paper,an adaptive segmentation model based on the U-Net framework is proposed for the lesion segmentation problem in ***,the model consists of three u-net frameworks that capture contextual features for 2 D and 3 D slices,respectively,and the outputs of different paths are integrated to obtain 3 D segmentation results through a two-stage voting ***,multiresolution constraints and dimensional information complementary strategies are introduced to alleviate the data heterogeneity problem and thus improve the accuracy of model *** experiments were conducted on the ISLES2015-SPES,ISLES2015-SISS and ISLES2017 datasets and submitted on the MICCAI Ischemic Stroke Lesion Segmentation(ISLES) platform to compare with other segmentation models,and the results show that the proposed model outperms the other models with promissing performance.

关键词： stroke multi-dimension multi-resolution segmentation

来源：评论

学校读者我要写书评

暂无评论

Autism Spectrum Disorder Recognition Based on Machine Learning with Roi Time-Series

SSRN

引用

SSRN 2023年

作者： Kang, Li Gong, Zhixin Huang, Jianjun Xu, Jinyang The College of Electronics and Information Engineering Shenzhen University Shenzhen518061 China The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen China

Autism spectrum disorders(ASD) is a neurodevelopmental disorder that causes repetitive steretyped behavior and social difficulties. Early diagnosis and intervention, especially, intelligent and reliable diagnosis can help with its treatment and recovery. However, The accuracy rate of the current intelligent diagnosis method can not meet the clinical requirement. To improve the accuracy of recognition of autism, in this paper, we propose a ROI time-series autism classification framework based on the combination of LSTM-attention and ResNet-SeNet module. The LSTM-attention module in the framework combines the LSTM and attention module, which could extract long term features and short term features more comprehensively, while the ResNet-SeNet module makes the network focus on valuable features and prevents network degradation. We evaluate the proposed framework on multiple atlases dataset preprocessed by Pearson correlation matrix and sliding window respectively and the voting strategy is introduced to further improve the classification accuracy. Experimental results indicate that our network could yield favorable diagnosis accuracies. Under two different preprocessing methods, our network outperforms other models with 73.1% accuracy on DOS brain atlas and 81.1% accuracy on HO brain atlas. In addition, we have constructed the brain functional connectivity topology of patients and normal people respectively for future research on autism. © 2023, The Authors. All rights reserved.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Channel-Vocoder-Centric Modelling of Cochlear Implants: Strengths and Limitations 9th

Channel-Vocoder-Centric Modelling of Cochlear Implants: Stre...

引用

9th Conference on Sound and Music Technology, CSMT 2021

作者： Kong, Fanhui Mo, Yefei Zhou, Huali Meng, Qinglin Zheng, Nengheng Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University Guangdong Shenzhen518060 China Acoustic Laboratory School of Physics and Optoelectronics South China University of Technology Guangdong Guangzhou510610 China School of Medicine South China University of Technology Guangdong Guangzhou510006 China

ISBN: (纸本)9789811947025

Modern cochlear implants (CIs) generate electric current pulsatile stimuli from real-time incoming to stimulate residual auditory nerves of deaf ears. In this unique way, deaf people can (re)gain a sense of hearing and consequent speech communication abilities. The electric hearing mimics the normal acoustic hearing (NH), but with a different physical interface to the neural system, which limits the performance of CI devices. Simulating the electric hearing process of CI users through NH listeners is an important step in CI research and development. Many acoustic modelling methods have been developed for simulation purposes, e.g., to predict the performance of a novel sound coding strategy. Channel vocoders with noise or sine-wave carriers are mostly popular among the methods. The simulation works have accelerated the procedures of re-engineering and understanding of the electric hearing. This paper presents an overview of the literature on channel-vocoder simulation methods. Strengths, limitations, applications, and future works about acoustic vocoder simulation methods are introduced and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cochlear implants

来源：评论

学校读者我要写书评

暂无评论

Multiple degraded image restoration via degradation history estimation

Multiple degraded image restoration via degradation history ...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Minhua Liu Yuanman Li Rongqin Liang Jiaxiang You Xia Li Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University China

Image restoration is a fundamental task in low-level computer vision. Most existing algorithms assume that the input image has a single known degradation type. In reality, images usually contain multiple degradations, making the restoration challenging. Though recent works restore the multiple degraded images, they assume that the degradation history is known. Obviously, such an ideal assumption often does not hold in real applications. This work proposes a novel restoration framework for multiple degraded images via degradation history estimation. Specifically, we first develop a sequential model to estimate the degradation history, including both the degradation operation chain and the corresponding parameters. By resorting to designed self-attention and cross-attention mechanisms, our method can effectively model the correlation of the input image, degradation operation chain, and parameters. Then, we apply our estimation framework for the multiple degraded image restoration, without requiring the degradation history. Experiment results demonstrate much better performance than existing approaches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Distributed Fixed-Time Algorithms for Time-Varying Constrained Optimization Problems

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年

作者： He, Xing Li, Yue Zhang, Meng Huang, Tingwen Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this paper, the distributed form of the zeroing neural network for solving time-varying optimal problems is put forward. Compared with traditional centralized algorithms, distributed algorithms possess better privacy and scalability. This paper initially proposes a centralized time-varying optimisation algorithm with fixed-time convergence and certain robustness, which is based on the integration-enhanced zeroing neural network. Subsequently, the algorithm is enhanced, and two distributed algorithms are designed separately. Both of these two algorithms have a fixed convergence time and certain robustness. Additionally, this paper utilizes the penalty function approach to handle time-varying optimization problems with inequality constraints, thereby making the algorithm more widely applicable. The effectiveness of the algorithm is verified through several numerical examples, and the applicability of the algorithm is demonstrated by solving the package-level state-of-charge balancing problem. © 2020 IEEE.

关键词： Optimization algorithms

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：