Federated learning for 6G-enabled secure communication systems: a comprehensive survey [0.03%]
面向6G的安全通信系统的联邦学习综述
Deepika Sirohi,Neeraj Kumar,Prashant Singh Rana et al.
Deepika Sirohi et al.
Machine learning (ML) and Deep learning (DL) models are popular in many areas, from business, medicine, industries, healthcare, transportation, smart cities, and many more. However, the conventional centralized training techniques may not a...
Video summarization using deep learning techniques: a detailed analysis and investigation [0.03%]
基于深度学习的视频摘要研究综述与分析
Parul Saini,Krishan Kumar,Shamal Kashid et al.
Parul Saini et al.
One of the critical multimedia analysis problems in today's digital world is video summarization (VS). Many VS methods have been suggested based on deep learning methods. Nevertheless, These are inefficient in processing, extracting, and de...
Multiple criteria decision analytic methods in management with T-spherical fuzzy information [0.03%]
基于T-球模糊信息的管理中多准则决策分析方法
Ting-Yu Chen
Ting-Yu Chen
With a focus on T-spherical fuzzy (T-SF) sets, the aim of this paper is to create a split-new appraisal mechanism and an innovative decision analytic method for use with multiple-criteria assessment and selection in uncertain situations. Th...
Medical image data augmentation: techniques, comparisons and interpretations [0.03%]
医学图像数据增强：方法、比较与解释
Evgin Goceri
Evgin Goceri
Designing deep learning based methods with medical images has always been an attractive area of research to assist clinicians in rapid examination and accurate diagnosis. Those methods need a large number of datasets including all variation...
A systematic review of the use of topic models for short text social media analysis [0.03%]
主题模型在短文本社交媒体分析中应用的系统性综述
Caitlin Doogan Poet Laureate,Wray Buntine,Henry Linger
Caitlin Doogan Poet Laureate
Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform w...
Ciyuan Peng,Feng Xia,Mehdi Naseriparsa et al.
Ciyuan Peng et al.
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately. As graph data, knowledge graphs accumulate and convey knowledg...
The role of artificial intelligence in developing a banking risk index: an application of Adaptive Neural Network-Based Fuzzy Inference System (ANFIS) [0.03%]
人工智能在开发银行风险指数中的作用：自适应神经网络模糊推理系统（ANFIS）的应用
Ibrahim Elsiddig Ahmed,Riyadh Mehdi,Elfadil A Mohamed
Ibrahim Elsiddig Ahmed
Banking risk measurement and management remain one of many challenges for managers and policymakers. This study contributes to the banking literature and practice in two ways by (a) proposing a risk ranking index based on the Mahalanobis Di...
The q-rung fuzzy LOPCOW-VIKOR model to assess the role of unmanned aerial vehicles for precision agriculture realization in the Agri-Food 4.0 era [0.03%]
基于q-水平模糊LOPTCOW-VIKOR模型评估无人机在农业4.0时代精准农业实施中的作用
Fatih Ecer,İlkin Yaran Ögel,Raghunathan Krishankumar et al.
Fatih Ecer et al.
Smart agriculture is gaining a lot of attention recently, owing to technological advancement and promotion of sustainable habits. Unmanned aerial vehicles (UAVs) play a crucial role in smart agriculture by aiding in different phases of agri...
Impact of word embedding models on text analytics in deep learning environment: a review [0.03%]
词嵌入模型对深度学习环境下文本分析影响的综述研究
Deepak Suresh Asudani,Naresh Kumar Nagwani,Pradeep Singh
Deepak Suresh Asudani
The selection of word embedding and deep learning models for better outcomes is vital. Word embeddings are an n-dimensional distributed representation of a text that attempts to capture the meanings of the words. Deep learning models utiliz...
Manuel Méndez,Mercedes G Merayo,Manuel Núñez
Manuel Méndez
Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is important to develop forecasting mechanisms that can be used by the authorities, so that they can anticipate measures when high concentrations of cert...