Image synthesis method based on multiple text description by NIE Kaiqin, NI Zhengwei

“…The optimized model was verified on the CUB and MS-COCO datasets, demonstrating the generation of images with intact structures, stronger semantic consistency, and richer visual diversity.…”
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Image tampering localization model for intensive post-processing scenarios by TAN Shunquan, LIAO Guiying, PENG Rongxuan, HUANG Jiwu

“…Notably, the model demonstrates exceptional robustness in assessments conducted with datasets representing diverse social media dissemination scenarios.…”
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Differential privacy protection scheme based on edge betweenness model by Haiping HUANG, Kai WANG, Xiong TANG, Dongjun ZHANG

“…With the continuous development of social network application,user’s personal social data is so sensitive that the problem of privacy protection needs to be solved urgently.In order to reduce the network data sensitivity,a differential privacy protection scheme BCPA based on edge betweenness model was proposed.The 2K sequence corresponding to the graph structure based on the dK model was captured,and 2K sequences based on the edge betweenness centrality were reordered.According to the result of reordering,the 2K sequence was grouped into several sub-sequences,and each sub-sequence was respectively added with noise by a dK perturbation algorithm.Finally,a social network graph satisfying differential privacy was generated according to the new 2K sequences after integration.Based on the real datasets,the scheme was compared with the classical schemes through simulation experiments.The results demonstrate that it improves the accuracy and usability of data while ensuring desired privacy protection level.…”
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Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest by I Gede Brawiswa Putra, Pei-Fen Kuo, Dominique Lord

“…In addition, most crash and POIs studies have utilized typical restaurant datasets instead of specific restaurants partnered with OFDS, which might bias the impact of traffic safety estimation. …”
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What Policy Evidence for a European Strategy of Sustainable Development in Mountain Regions? by Erik Gløersen, Clemens Mader, Engelbert Ruoss

“…Mountain territories have highly diverse social, economic and physical characteristics; their shared traits in terms of ecological fragility, economic development challenges and exposure to natural hazards are not reflected in mainstream datasets. Two complementary instruments are proposed to produce and present evidence for sustainable resource management and processes: the Nexus Model and the Sustainability Profile Matrix. …”
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Abnormal traffic detection method based on multi-scale attention feature enhancement by YANG Hongyu, ZHANG Haohao, CHENG Xiang

“…Experimental results on the CIC-IDS2017 and CSE-CIC-IDS2018 datasets show that the proposed method improves F1 score by 0.17% to 2.75% and 0.43% to 8.99%, respectively, which has good detection performance.…”
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Super-resolved microstructure of pyrolyzing superlight ablators by Collin W. Foster, Sreevishnu Oruganti, Francesco Panerai

“…A super-resolution methodology was implemented, where high-resolution tomography scans were applied to denoise, segment and analyze lower-resolution in situ datasets that captured a large field of view. This multi-scale approach enabled the quantification of morphological and effective properties as a function of temperature during degradation, while also relating these changes to relevant decomposition chemistry. …”
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Dual-Targeted adversarial example in evasion attack on graph neural networks by Hyun Kwon, Dae-Jin Kim

“…We provide a detailed explanation of the method’s principles and structure, rigorously evaluate its effectiveness across several GNN models, and visualize the impact using datasets such as Reddit and OGBN-Products. Our contributions highlight the potential for dual-targeted attacks to disrupt GNN performance and emphasize the need for enhanced defensive strategies in graph-based learning systems.…”
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EC-Structure: Establishing Consumption Structure through Mining E-Commerce Data to Discover Consumption Upgrade by Lin Guo, Dongliang Zhang

“…The experiments prove the efficacy of the algorithm proposed in this paper compared to other similar algorithms using several different datasets, which illustrates the algorithm’s efficacy and stable performance in consumption structure analysis.…”
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Accelerated unconstrained latent factorization of tensor model for Web service QoS estimation by Mingwei LIN, Wenqiang LI, Xiuqin XU, Jian LIU

“…Aiming at the problem that the Web service quality of service (QoS) estimation methods based on the non-negative latent factorization of tensor model (NLFT) depend heavily on non-negative initial random data and specially designed non-negative training schemes, which lead to low compatibility and scalability, an accelerated unconstrained latent factorization of tensor (AULFT) model was proposed.The proposed model consisted of three main parts.The non-negative constraints from decision parameters were transferred to output latent factors and they were connected through the single-element-dependent mapping function.A momentum-incorporated stochastic gradient descent (MSGD) algorithm was used to effectively improve the convergence rate and estimation accuracy of the proposed AULFT model.The detailed algorithm and result analysis of the proposed AULFT model were presented.The empirical study on two dynamic QoS datasets in real industrial applications demonstrates that the proposed AULFT model has higher computational efficiency and estimation accuracy than the state-of-the-art QoS estimation models.…”
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Internet intelligent routing architecture and algorithm by Fei GUI, Yang CHENG, Dan LI, Sihong HONG

“…Experiments on two open-source datasets demonstrate that the proposed scheme can reduce utilization of bottleneck link by 13%～70%, compared with the baselines.…”
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Adaptive clustering federated learning via similarity acceleration by Suxia ZHU, Binke GU, Guanglu SUN

“…In order to solve the problem of model performance degradation caused by data heterogeneity in the federated learning process, it is necessary to consider personalizing in the federated model.A new adaptively clustering federated learning (ACFL) algorithm via similarity acceleration was proposed, achieving adaptive acceleration clustering based on geometric properties of local updates and the positive feedback mechanism during clients federated training.By dividing clients into different task clusters, clients with similar data distribution in the same cluster was cooperated to improve the performance of federated model.It did not need to determine the number of clusters in advance and iteratively divide the clients, so as to avoid the problems of high computational cost and slow convergence speed in the existing clustering federation methods while ensuring the performance of models.The effectiveness of ACFL was verified by using deep convolutional neural networks on commonly used datasets.The results show that the performance of ACFL is comparable to the clustered federated learning (CFL) algorithm, it is better than the traditional iterative federated cluster algorithm (IFCA), and has faster convergence speed.…”
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Performance of Multimodel Schemes for Seasonal Precipitation over Indian Region by Vinay Kumar, Tirthankar Ghosh

“…This study uses downscaled rainfall datasets from 16 coupled climate models at high resolution of 25 km from 1987 to 2001. …”
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Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics by Lulu Shang, Peijun Wu, Xiang Zhou

“…Applied to five real datasets, Celina uncovers ct-SVGs associated with tumor progression and patient survival in lung cancer, identifies metagenes with unique spatial patterns linked to cell proliferation and immune response in kidney cancer, and detects genes preferentially expressed near amyloid-β plaques in an Alzheimer’s model.…”
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Human Pose Estimation: Single-Person and Multi-Person Approaches by Tang Wan

“…In addition, this paper analyzes commonly used datasets relevant to HPE, discusses the current unsolved issues, and forecasts future research directions, with the aim of providing valuable references and guidance for subsequent research in this field.…”
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Infrared Thermal Image Gender Classifier Based on the Deep ResNet Model by Alyaa J. Jalil, Naglaa M. Reda

“…It proposes a unique approach called IRT_ResNet that adopts residual network (ResNet) model with different layer configurations: 18, 50, and 101. Two different datasets of thermal images have been leveraged to train and test these models. …”
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Self-Attention Multilayer Feature Fusion Based on Long Connection by Chu Yuezhong, Wang Jiaqing, Liu Heng

“…In order to verify the effectiveness of the model, the image classification experiment was done on a number of typical datasets. The experimental results prove that the model can fit the existing convolutional neural network well and effectively improve the classification accuracy of the convolutional network only at the cost of a small amount of calculation.…”
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Artificial Intelligence-Based Digital Media Design Effect Enhancement Mechanism by Pu Zhao

“…Finally, we verify the effectiveness of the proposed method on two datasets, namely, PASCAL VOC and MIT-Adobe FiveK. The results show that our proposed method performs well in the process of evaluation.…”
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Learning-Based Path Planning Algorithm in Ocean Currents for Multi-Glider by Wei Lan, Xiang Jin, Xin Chang, Tianlin Wang, Han Zhou

“…The algorithm architecture is compared and tested on two datasets, grid maps and ocean maps. Doc-CNN has an advantage over architecture without being tailored to glider characteristics and makes full use of known global information and local information collected by gliders themselves. …”
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IMPROVING PREDICTION ACCURACY OF DEEP LEARNING FOR BRAIN CANCER DIAGNOSIS USING POLYAK-RUPPERT OPTIMIZATION by M Muthulekshmi, Azath Mubarakali, Y M Blessy

“…Recent advancements in deep learning have significantly enhanced diagnostic capabilities, but challenges persist in optimizing model performance for diverse and complex datasets. This study investigates the application of Polyak-Ruppert Optimization (PRO) to improve the prediction accuracy of conventional deep learning models for brain cancer diagnosis. …”
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