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Comparison of CNN-based deep learning architectures for rice diseases classification

Artificial Intelligence in Agriculture 2023年第3期9卷 22-35页

作者： Md Taimur Ahad Yan Li Bo Song Touhid Bhuiyan Department of Computer Science and Engineering Daffodil International UniversitySavarBangladesh School of Mathematics Physics and Computing University of Southern QueenslandToowoombaAustralia School of Engineering University of Southern Queensland ToowoombaAustralia Department of Computer Science and Engineering Faculty of Science and Information TechnologyDaffodil International UniversityBangladesh

Although convolutional neural network(CNN)paradigms have expanded to transfer learning and ensemble models from original individual CNN architectures,few studies have focused on the performance comparison of the applicability of these techniques in detecting and localizing rice ***,most CNN-based rice disease detection studies only considered a small number of diseases in their *** these shortcomings were addressed in this *** this study,a rice disease classification comparison of six CNN-based deep-learning architectures(DenseNet121,Inceptionv3,MobileNetV2,resNext101,Resnet152V,and Seresnext101)was conducted using a database of nine of the most epidemic rice diseases in *** addition,we applied a transfer learning approach to DenseNet121,MobileNetV2,Resnet152V,Seresnext101,and an ensemble model called DEX(Densenet121,EfficientNetB7,and Xception)to compare the six individual CNN networks,transfer learning,and ensemble *** results suggest that the ensemble framework provides the best accuracy of 98%,and transfer learning can increase the accuracy by 17%from the results obtained by Seresnext101 in detecting and localizing rice leaf *** high accuracy in detecting and categorisation rice leaf diseases using CNN suggests that the deep CNN model is promising in the plant disease detection domain and can significantly impact the detection of diseases in real-time agricultural *** research is significant for farmers in rice-growing countries,as like many other plant diseases,rice diseases require timely and early identification of infected diseases and this research develops a rice leaf detection system based on CNN that is expected to help farmers to make fast decisions to protect their agricultural yields and quality.

关键词： Deep learning Convolutional neural networks(CNNs) Transfer learning Plant leaf disease detection

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Speech Emotion Recognition based on Semi-Supervised Adversarial Variational Autoencoder 10

Speech Emotion Recognition based on Semi-Supervised Adversar...

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10th IEEE International Conference on Cyber Security and Cloud Computing and 9th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Xiao, Yufeng Bo, Yuqin Zheng, Zhiling Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan China Hunan Industry Polytechnic Information Center Changsha China

ISBN: (纸本)9798350312461

The application of semi-supervised learning in the field of speech emotion recognition can alleviate the problem of dependence on the amount of labeled data. Its core assumption is that the labeled and unlabeled data have the same feature representations, which determine the performance of the models. Therefore, this paper proposes a novel speech emotion recognition model based on semi-supervised adversarial variational autoencoding (SSAVAE), which reaps the advantages of generative adversarial network(GAN) and variational autoencoding(VAE) to learn the distribution of input data in the feature space. On the one hand, it can overcome the disturbance of the input data through learning the distribution of the input data in the feature space. On the other hand, it can approximate arbitrary feature distribution by introducing GAN. Concretely, SSAVAE considers the unlabeled data as the problem of the lack of emotional label attributes. The labeled data share the category information with the unlabeled data in the feature space. Several experiments are conducted on the FAU Aibo dataset to evaluate the effectiveness of the algorithm. The results show that the proposed method is superior to other benchmark algorithms and has strong feature learning capabilities. © 2023 IEEE.

关键词： Emotion Recognition

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Contrastive Learning of Sequential Recommendation with Graph Attention Mechanisms 5

Contrastive Learning of Sequential Recommendation with Graph...

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5th International Conference on computer engineering and Intelligent Control, ICCEIC 2024

作者： Xie, Xu Chen, Rongyuan College of Computer Science Hunan University of Technology and Business Hunan Changsha China School of Resource & Environment Hunan University of Technology and Business Hunan Changsha China

ISBN: (纸本)9798331507992

Sequential recommendation models the dynamic interest changes of users based on their interaction information with items, in order to predict the next interaction item for users. Existing sequential recommendation algorithms are susceptible to data sparsity issues. Contrastive learning sequential recommendation effectively alleviates data sparsity issues through construct samples and data enhancement methods, but it faces data noise problems. In response to the problem of introducing data noise in contrastive learning sequence recommendation, a graph attention mechanism-based contrastive learning sequential recommendation model (GACLRec) is proposed. This model uses the graph attention mechanism to dynamically evaluate and weight the importance of different neighboring nodes, effectively suppressing the interference of noise information and achieving interpretable aggregation of information from neighboring nodes. On this basis, in order to obtain richer node representations, the model further improved the multi-head graph attention mechanism to learn the diverse representations of nodes in multiple latent spaces. By integrating these representations from different spaces, a comprehensive node feature vector is finally obtained, enabling the model to comprehensively learn the actual preferences and behavior patterns of users. Compared with existing excellent algorithms on the real datasets, the beauty and yelp. The experiment proves that the model proposed in this paper has a certain improvement compared to the baseline method on the evaluation metrics HR@N and NDCG@N. © 2024 IEEE.

关键词： Contrastive Learning

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Elite-guided equilibrium optimiser based on information enhancement:Algorithm and mobile edge computing applications

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CAAI Transactions on Intelligence technology 2024年第5期9卷 1126-1171页

作者： Zong-Shan Wang Shi-Jin Li Hong-Wei Ding Gaurav Dhiman Peng Hou Ai-Shan Li Peng Hu Zhi-Jun Yang Jie Wang School of Information Science and Engineering Yunnan UniversityKunmingChina Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhenChina Academic Affairs Office Yunnan University of Finance and EconomicsKunmingChina Faculty of Management and Economics Kunming University of TechnologyKunmingChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirutLebanon Department of Computer Science and Engineering University Centre for Research and DevelopmentChandigarh UniversityChennaiIndia Department of Computer Science and Engineering Graphic Era Deemed to Be UniversityDehradunIndia School of Computer Science Fudan UniversityShanghaiChina Rackham Graduate School University of MichiganAnn ArborMIUSA Research and Development Department Youbei Technology Co.LTDKunmingChina School of Mechanical and Power Engineering Zhengzhou UniversityZhengzhouChina

The Equilibrium Optimiser(EO)has been demonstrated to be one of the metaheuristic algorithms that can effectively solve global optimisation *** the paradox between exploration and exploitation operations while enhancing the ability to jump out of the local optimum are two key points to be addressed in EO *** alleviate these limitations,an EO variant named adaptive elite-guided Equilibrium Optimiser(AEEO)is ***,the adaptive elite-guided search mechanism enhances the balance between exploration and *** modified mutualism phase reinforces the information interaction among particles and local optima *** cooperation of these two mechanisms boosts the overall performance of the basic *** AEEO is subjected to competitive experiments with state-of-the-art algorithms and modified algorithms on 23 classical benchmark functions and IEE CEC 2017 function test *** results demonstrate that AEEO outperforms several well-performing EO variants,DE variants,PSO variants,SSA variants,and GWO variants in terms of convergence speed and *** addition,the AEEO algorithm is used for the edge server(ES)placement problem in mobile edge computing(MEC)*** experimental results show that the author’s approach outperforms the representative approaches compared in terms of access latency and deployment cost.

关键词： ANT COLONY optimization CLOUD COMPUTING GENETIC ALGORITHMS SWARM intelligence

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Edge-Coordinated Energy-Efficient Video Analytics for Digital Twin in 6G

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China Communications 2023年第2期20卷 14-25页

作者： Peng Yang Jiawei Hou Li Yu Wenxiong Chen Ye Wu School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhanHubei 430074China College of Information Science and Engineering Hunan Normal UniversityChangshaHunan 410081China School of Advanced Technology Xi’an Jiaotong-Liverpool UniversitySuzhouJiangsu 215123China

Camera networks are essential to constructing fast and accurate mapping between virtual and physical space for digital *** this paper,with the aim of developing energy-efficient digital twin in 6G,we investigate real-time video analytics based on cameras mounted on mobile devices with edge *** problem is challenging because 1)mobile devices are with limited battery life and lightweight computation capability,and 2)the captured video frames of mobile devices are continuous changing,which makes the corresponding tasks arrival *** achieve energy-efficient video analytics in digital twin,by taking energy consumption,analytics accuracy,and latency into consideration,we formulate a deep reinforcement learning based mobile device and edge coordination video analytics framework,which can utilized digital twin models to achieve joint offloading decision and configuration *** edge nodes help to collect the information on network topology and task *** simulation results demonstrate that our proposed framework outperforms the benchmarks on accuracy improvement and energy and latency reduction.

关键词： mobile edge computing video analytics digital twin 6G deep reinforcement learning

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KeyEE:Enhancing Low-Resource Generative Event Extraction with Auxiliary Keyword Sub-Prompt

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Big Data Mining and Analytics 2024年第2期7卷 547-560页

作者： Junwen Duan Xincheng Liao Ying An Jianxin Wang Hunan Key Laboratory of Bioinformatics School of Computer Science and EngineeringCentral South UniversityChangsha 410083China Big Data Institute Central South UniversityChangsha 410083China

Event Extraction(EE)is a key task in information extraction,which requires high-quality annotated data that are often costly to *** classification-based methods suffer from low-resource scenarios due to the lack of label semantics and fine-grained *** recent approaches have endeavored to address EE through a more data-efficient generative process,they often overlook event keywords,which are vital for *** tackle these challenges,we introduce KeyEE,a multi-prompt learning strategy that improves low-resource event extraction by Event Keywords Extraction(EKE).We suggest employing an auxiliary EKE sub-prompt and concurrently training both EE and EKE with a shared pre-trained language *** the auxiliary sub-prompt,KeyEE learns event keywords knowledge implicitly,thereby reducing the dependence on annotated ***,we investigate and analyze various EKE sub-prompt strategies to encourage further research in this *** experiments on benchmark datasets ACE2005 and ERE show that KeyEE achieves significant improvement in low-resource settings and sets new state-of-the-art results.

关键词： natural language processing Event Extraction(EE) Multi-Prompt Learning(MPL) low-resource

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Overcoming Spatial Constraints in VR:A Survey of Redirected Walking Techniques

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Journal of computer science & technology 2024年第4期39卷 841-870页

作者： Jia-Hong Liu Yang-Fu Ren Qi Wen Gan Kui Huang Fiona Xiao Yu Chen Er-Xia Luo Khang Yeu Tang Yue-Yao Fu Cheng-Wei Fan Sen-Zhe Xu Song-Hai Zhang Academy of Arts and Design Tsinghua UniversityBeijing 100084China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China College of Computer Technology and Application Qinghai UniversityXining 810016China Zhili College Tsinghua UniversityBeijing 100084China School of Computer Beijing Information Science and Technology UniversityBeijing 100192China Department of Physics Tsinghua UniversityBeijing 100084China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China

As the virtual reality(VR)technology strives to provide immersive and natural user experiences,the challenge of aligning vast virtual environments with limited physical spaces remains *** survey comprehensively explores the advancements in redirected walking(RDW)techniques aimed at overcoming spatial constraints in *** addresses this by subtly manipulating users’physical movements to allow for seamless navigation within constrained *** survey delves into gain perception mechanisms,detailing how slight discrepancies between virtual and real-world movements can be utilized without user awareness,thus extending the effective navigable *** RDW control algorithms for gain-based RDW are analyzed,highlighting their implementation and effectiveness in maintaining immersion and minimizing perceptual ***,novel methods extending beyond traditional gain-based techniques are discussed,showcasing innovative approaches that further refine VR *** practical implications of RDW in enhancing safety and reducing physical collisions in VR environments are underscored,alongside its potential to improve user experience by aligning virtual exploration more closely with natural human behavior *** a thorough review of existing literature and recent advancements,this survey provides a systematic understanding for researchers,developers,and industry *** underscores the importance of RDW in the future of VR,emphasizing RDW's role in making VR more accessible and practical across various applications,from education and training to therapy and *** paper concludes with a forward-looking perspective on the continued evolution and potential of RDW in revolutionizing virtual reality experiences.

关键词： virtual reality(VR) redirected walking(RDW) redirection gain perception

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Impacts of canopy structure on the sub-canopy solar radiation under a deciduous forest based on fisheye photographs

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Research in Cold and Arid Regions 2023年第3期15卷 150-160页

作者： YanLin Zhang XiaoLin Feng XiaoLi Chang LiMin Tie School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtanHunan 411201China

Forest canopy in a deciduous forest has significant sheltering effects on the sub-canopy solar radiation,significantly influencing the energy balance of snow and permafrost beneath the forest and their spatial *** study employs a digital camera mounted with a fisheye lens to acquire photographs at various times in a growth cycle of the forest canopy at three selected sites in a deciduous forest near the Greater Khingan Mountains Forest Ecological Station,Northeast *** vegetation types and conditions at the selected sites include P1 in ***,P2 in Carex ***,and P3 in Betula *** necessary image processing,these photographs were used to identify the canopy structure and its impacts on the sub-canopy solar *** show that fisheye photographs can successfully capture the forest canopy structure and are useful in estimating the sub-canopy solar *** order of sheltering effects from the largest to the smallest on sub-canopy solar radiation at three selected sites is P3,P1,and P2,highly depending on the canopy *** sub-canopy solar radiation was calculated using fisheye photographs and an algorithm validated by in-situ observed solar radiation beneath the canopy at P1 and *** results are reasonable,although the accuracy seems compromised due to the mismatch of conditions for calculation and *** also show that the mean annual solar radiation above the canopy was about 148.3 W/m2 in 2018,and the mean annual solar radiation values beneath the canopy were about 90.0,123.8,and 61.0 W/m2 at P1,P2,and P3,with only 60%,84%,and 42%of the total solar radiation penetrating through the canopy,*** in winter,when the trees are leafless,the canopy sheltering effects cannot be ignored in dense *** the limitations,fisheye photographs and related algorithms are useful in investigating the forest canopy structure and its impacts on sub-canopy s

关键词： Solar radiation Forest structure Fisheye photograph Sub-canopy Deciduous forest

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LV-auth: Lip Motion Fusion for Voiceprint Authentication 18th

LV-auth: Lip Motion Fusion for Voiceprint Authentication

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18th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Liu, Wei Zhu, Xiaojing Liu, Qin Li, Peng Zhou, Man School of Cyber Science and Engineering Wuhan University Wuhan430072 China School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783031714634

Voiceprint authentication is a growing field of biometric authentication. However, voiceprint authentication is vulnerable to spoofing attacks and suffers significant degradation in noisy environments. Employing lip motion detection is an innovative solution to enhance security. By strategically selecting a clean channel, such as the ultrasonic frequencies generated by smartphones’ inherent audio capability, lip motion detection can be performed without disturbance from ambient noise. In this paper, we propose LV-auth, a smartphone-based multimodal biometric authentication system that integrates lip motion and voiceprint. LV-auth captures both the speech signals and the ultrasonic echo signals modulated by lip motion, enabling liveness detection while enhancing robustness. We employ a contrastive learning-based feature extractor to extract reliable and effective fused features from both modalities for authentication. Extensive experiments show that LV-auth achieves an authentication accuracy of 99.37% and an equal error rate (EER) of 0.73% on the smartphone. In particular, LV-auth demonstrates excellent robustness in noisy environments and effectively withstands spoofing attacks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Smartphones

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On the parameterized complexity of minimum/maximum degree vertex deletion on several special graphs

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Frontiers of computer science 2023年第4期17卷 97-107页

作者： Jia LI Wenjun LI Yongjie YANG Xueying YANG School of Information Engineering Hunan Industry PolytechnicChangsha 410036China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication EngineeringChangsha University of Science and TechnologyChangsha 410015China Chair of Economic Theory Saarland UniversitySaarbrücken 66123Germany

In the minimum degree vertex deletion problem,we are given a graph,a distinguished vertex in the graph,and an integer κ,and the question is whether we can delete at most κ vertices from the graph so that the distinguished vertex has the unique minimum *** maximum degree vertex deletion problem is defined analogously but here we want the distinguished vertex to have the unique maximum *** is known that both problems areΨ-hard and fixed-parameter intractable with respect to some natural *** this paper,we study the(parameterized)complexity of these two problems restricted to split graphs,p-degenerate graphs,and planar *** study provides a comprehensive complexity landscape of the two problems restricted to these special graphs.

关键词： minimum degree maximum degree vertex deletion split graphs planar graphs parameterized complexity

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