Titlebook: Big Data and Security; 5th International Co Yuan Tian,Tinghuai Ma,Muhammad Khurram Khan Conference proceedings 2024 The Editor(s) (if appli

到凝乳

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

Lacerate

Big Data and Security978-981-97-4387-2Series ISSN 1865-0929 Series E-ISSN 1865-0937

行業(yè)

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..

脾氣暴躁的人

https://doi.org/10.1007/978-981-97-4387-2Security and Privacy; Big Data; Block Chain; Distributed computing methodologies; Security Services; Intr

Fibrin

flavonoids

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

exacerbate

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

Lipoma

,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

MILL

藕床生厭倦