標(biāo)題: Titlebook: Big Data and Security; 5th International Co Yuan Tian,Tinghuai Ma,Muhammad Khurram Khan Conference proceedings 2024 The Editor(s) (if appli [打印本頁] 作者: 到凝乳 時間: 2025-3-21 19:47
書目名稱Big Data and Security影響因子(影響力)
書目名稱Big Data and Security影響因子(影響力)學(xué)科排名
書目名稱Big Data and Security網(wǎng)絡(luò)公開度
書目名稱Big Data and Security網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Big Data and Security被引頻次
書目名稱Big Data and Security被引頻次學(xué)科排名
書目名稱Big Data and Security年度引用
書目名稱Big Data and Security年度引用學(xué)科排名
書目名稱Big Data and Security讀者反饋
書目名稱Big Data and Security讀者反饋學(xué)科排名
作者: Lacerate 時間: 2025-3-21 22:28
Big Data and Security978-981-97-4387-2Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 行業(yè) 時間: 2025-3-22 00:26
Conference proceedings 2024ina, during December?22–24, 2023.?..The 35 full papers and 1 short paper were carefully reviewed and selected from 161 submissions. They are organized in topical sections as follows:?..Part One:?Big Data & New Method and?Artificial Intelligence & Machine Learning..Part Two:?Data Technology & Network Security and?IoT Security & Privacy Protection..作者: 脾氣暴躁的人 時間: 2025-3-22 05:43
https://doi.org/10.1007/978-981-97-4387-2Security and Privacy; Big Data; Block Chain; Distributed computing methodologies; Security Services; Intr作者: Fibrin 時間: 2025-3-22 08:46 作者: flavonoids 時間: 2025-3-22 14:18
https://doi.org/10.1007/3-540-34011-4ecognition often focuses on facial features from single facial images, without taking into account personal aging patterns. We propose an algorithm for personal aging patterns based on manifold learning (MLPAP). MLPAP combines manifold learning and two deep learning architecture Convolutional Neural作者: exacerbate 時間: 2025-3-22 19:56
Untersuchungsmethoden der Mikrostruktur,dependencies, limiting their generality and scalability in real engineering projects. To address this issue, this paper introduces a Three Layer Chinese Sentiment Polarity Detection Framework (.). This framework decouples the final polarity detection from language processing by dividing the task int作者: Lipoma 時間: 2025-3-22 21:42
,Teilchengeh?rtete Legierungen,lectual output is a key representation of discipline construction. We created an algorithm to identify development features of disciplines, including temporal trend, research hotspots, and mutation characteristics. Using CNKI as data source, with the aid of scientific knowledge graph and social netw作者: MILL 時間: 2025-3-23 01:24 作者: 藕床生厭倦 時間: 2025-3-23 09:36 作者: NOVA 時間: 2025-3-23 11:29 作者: 懲罰 時間: 2025-3-23 17:23 作者: 高腳酒杯 時間: 2025-3-23 18:56 作者: constellation 時間: 2025-3-24 02:10 作者: 憤怒事實 時間: 2025-3-24 05:43 作者: 擴大 時間: 2025-3-24 06:46
,übergang in den festen Zustand,t of panoramic segmentation technology. It has a wide range of applications in many areas, such as cyber security, intelligent driving, tumor recognition, boundary segmentation, pest, disease recognition, face recognition and beauty enhancement, etc. With the continuous development of deep learning,作者: 委托 時間: 2025-3-24 14:29
,übergang in den festen Zustand,. It has gained substantial attention due to its versatile applications in virtual reality, augmented reality, medicine, cultural heritage preservation, intelligent transportation, and autonomous driving. Advancements in computational power, deep learning, and sensor technology have markedly improve作者: 扔掉掐死你 時間: 2025-3-24 15:30
Strukturelle Phasenumwandlungen,ncreasing awareness of data privacy and legal restrictions, the phenomenon of “data silos” has emerged. To overcome this issue, federated learning methods have been introduced. Federated learning emphasizes privacy protection and decentralization by allowing multiple participants to collaboratively 作者: Arteriography 時間: 2025-3-24 19:35
,übergang in den festen Zustand,ty that the agent may need to estimate the value of unseen action, which usually results in value overestimation and training instability. The Imitation-learning-based method, which is easy to implement and scale up, bypasses this problem by performing some kind of imitation learning on the dataset 作者: 大暴雨 時間: 2025-3-25 01:39 作者: 相反放置 時間: 2025-3-25 05:40
https://doi.org/10.1007/978-3-662-57763-9ing capabilities of deep learning, attribute graph clustering has emerged as a crucial method for dealing with complex network structures. In the field of network information security, a profound understanding and accurate classification of complex networks are particularly critical. In this article作者: analogous 時間: 2025-3-25 08:24
,Teilchengeh?rtete Legierungen, performance management, and will soon occupy a place in HR planning, training and development, and employee service, and will realize the high intelligence of HR service in the future. Therefore, this paper puts forward a demand forecasting model of HR professional structure based on DL. Firstly, B作者: Loathe 時間: 2025-3-25 11:50 作者: Malaise 時間: 2025-3-25 16:33
A Three Layer Chinese Sentiment Polarity Detection Framework with Case Studydependencies, limiting their generality and scalability in real engineering projects. To address this issue, this paper introduces a Three Layer Chinese Sentiment Polarity Detection Framework (.). This framework decouples the final polarity detection from language processing by dividing the task int作者: ESPY 時間: 2025-3-25 21:02
Big Data Intelligence Empowered Specialized Disciplines Development Pattern Recognition in Power Indlectual output is a key representation of discipline construction. We created an algorithm to identify development features of disciplines, including temporal trend, research hotspots, and mutation characteristics. Using CNKI as data source, with the aid of scientific knowledge graph and social netw作者: CLAIM 時間: 2025-3-26 03:34 作者: 清洗 時間: 2025-3-26 06:12
A Clustering Method for Distribution Network Load Curve Based on Fast DDTWh, particularly when handling curve data with varying lengths and shapes. This paper suggests a load clustering approach based on the combination of the K-medoids and Fast DDTW clustering methods because the DDTW distance computation is too complicated. The user load curve‘s distance is computed usi作者: Ossification 時間: 2025-3-26 08:47 作者: 情感 時間: 2025-3-26 12:39 作者: 突變 時間: 2025-3-26 20:31
Advances, Patterns and Future Potential of Big Data Technology Research for New Energy Sources and Ehis article explores the application of big data (BD) technologies in new energy power (NEP) and energy storage systems (ESS) in great depth. It also looks at how BD technology is now being used to grid management, electricity generation, and consumer usage. It presents development trends for the fu作者: depreciate 時間: 2025-3-27 00:26 作者: 秘密會議 時間: 2025-3-27 02:45
Analysing Potential of?ResNet for?Transfer Learning with?Stochastic Depthustness of ResNet models with stochastic depth when subjected to a common transfer learning technique: pruning the final layers. Our hypothesis claims that implementing the stochastic depth training approach is a preventive measure against co-adaptation among sequential layers. Consequently, this pr作者: 單挑 時間: 2025-3-27 06:30
A Survey of Research Progresses on Instance Segmentation Based on Deep Learningt of panoramic segmentation technology. It has a wide range of applications in many areas, such as cyber security, intelligent driving, tumor recognition, boundary segmentation, pest, disease recognition, face recognition and beauty enhancement, etc. With the continuous development of deep learning,作者: Microgram 時間: 2025-3-27 12:26 作者: 健忘癥 時間: 2025-3-27 17:40 作者: uveitis 時間: 2025-3-27 18:01
ROMA: Reverse Model-Based Data Augmentation for Offline Reinforcement Learningty that the agent may need to estimate the value of unseen action, which usually results in value overestimation and training instability. The Imitation-learning-based method, which is easy to implement and scale up, bypasses this problem by performing some kind of imitation learning on the dataset 作者: facilitate 時間: 2025-3-27 23:37 作者: Leisureliness 時間: 2025-3-28 05:27
Deep Learning-Based Attribute Graph Clustering: An Overviewing capabilities of deep learning, attribute graph clustering has emerged as a crucial method for dealing with complex network structures. In the field of network information security, a profound understanding and accurate classification of complex networks are particularly critical. In this article作者: depreciate 時間: 2025-3-28 09:13
Construction of Demand Forecasting Model of Human Resources Professional Structure Based on Deep Lea performance management, and will soon occupy a place in HR planning, training and development, and employee service, and will realize the high intelligence of HR service in the future. Therefore, this paper puts forward a demand forecasting model of HR professional structure based on DL. Firstly, B作者: vocation 時間: 2025-3-28 11:25
,Teilchengeh?rtete Legierungen,on should characterize the pattern of disciplinary development. This study is an attempt of specialized disciplines development pattern recognition by big data intelligence, and the recognition algorithms can be used for feature recognition in multidisciplinary fields.作者: 兒童 時間: 2025-3-28 17:08
Untersuchungsmethoden der Mikrostruktur, (YOLOv7), it is proposed that attention mechanism should be taken into account after three characteristic graphs are output to its backbone network, and the model structure with the highest accuracy can be obtained through comparative experiments of control variables. The experimental results show 作者: 正面 時間: 2025-3-28 22:21
Werkstoffe im Vergleich und Verbund,or malfunctions. It is critically hindering prediction accuracy. Therefore, this paper employs and compares various imputation techniques to handle missing data in gas regulator datasets. Through this process, the robustness of the accident prevention system can be improved.作者: prostate-gland 時間: 2025-3-29 00:41 作者: 不能和解 時間: 2025-3-29 05:33
Untersuchungsmethoden der Mikrostruktur, when the pruning of the last layers was conducted from the second layer of the fourth block to the second layer of the third block. This observation was made for both the CIFAR-10 and Oxford-IIIT Pet datasets. Furthermore, it was noted that there was no significant decline in the performance of the作者: Deject 時間: 2025-3-29 08:54 作者: 使激動 時間: 2025-3-29 12:41 作者: BILK 時間: 2025-3-29 17:21 作者: 共棲 時間: 2025-3-29 22:58
https://doi.org/10.1007/978-3-662-57763-9nteract to enhance clustering quality and model robustness. Contrastive methods improve clustering effectiveness by comparing the similarity or dissimilarity between different data points using similarity metrics. Finally, we point out several potential challenges and directions in the field of deep作者: micturition 時間: 2025-3-30 03:44 作者: 國家明智 時間: 2025-3-30 04:21
Big Data Intelligence Empowered Specialized Disciplines Development Pattern Recognition in Power Indon should characterize the pattern of disciplinary development. This study is an attempt of specialized disciplines development pattern recognition by big data intelligence, and the recognition algorithms can be used for feature recognition in multidisciplinary fields.作者: Classify 時間: 2025-3-30 10:14
Object Detection Model Based on?Attention Mechanism (YOLOv7), it is proposed that attention mechanism should be taken into account after three characteristic graphs are output to its backbone network, and the model structure with the highest accuracy can be obtained through comparative experiments of control variables. The experimental results show 作者: 止痛藥 時間: 2025-3-30 16:01 作者: 狗窩 時間: 2025-3-30 17:21 作者: 清醒 時間: 2025-3-30 22:23 作者: Musket 時間: 2025-3-31 03:53
Charting the?Landscape of?Multi-view Stereo: An In-Depth Exploration of?Deep Learning Techniquesrelated scenarios is currently a hot topic. In intelligent transportation and autonomous driving, it enhances traffic safety and navigation accuracy by modeling road and traffic conditions. In medicine, it improves surgical safety through surgical navigation and virtual surgical simulation. In cultu作者: 不感興趣 時間: 2025-3-31 07:30
ROMA: Reverse Model-Based Data Augmentation for Offline Reinforcement Learningment in a self-supervised way and can splice shortcuts inside each offline trajectory to augment their return value. Experiments on two navigation tasks demonstrate the effectiveness of ROMA, it can effectively optimize trajectory quality and significantly improve the performance of multiple IL-base作者: 明智的人 時間: 2025-3-31 11:39 作者: 勾引 時間: 2025-3-31 14:12 作者: 摘要記錄 時間: 2025-3-31 18:20
Construction of Demand Forecasting Model of Human Resources Professional Structure Based on Deep Lean AUC than only using artificial neural network model to extract features for text matching. Forecasting the demand of HR professional structure based on DL model can provide data support for enterprises to study the change and trend of talent demand in the field, and provide decision-making basis f
