It discusses the importance of transforming big data into valuable information through the analysis of machine and deep learning techniques. The article focuses on three key themes: advances in plant disease detection and crop health monitoring, integration of Artificial Intellige...
Recent Advancement and Challenges in Deep Learning, Big Data in Bioinformatics Chapter © 2022 References Haugeland J (1985) Artificial intelligence: the very idea Google Scholar Fukushima K, Miyake S (1982) Neocognitron: a self-organizing neural network model for a mechanism of visual pattern...
Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identifica
www.nature.com/npjcompumats REVIEW ARTICLE OPEN Recent advances and applications of deep learning methods in materials science Kamal Choudhary 1,2,3 ✉, Brian DeCost 4, Chi Chen 5, Anubhav Jain 6, Francesca Tavazza 1, Ryan Cohn 7, Cheol Woo Park8, Alok Choudhary9, Ankit Agrawal9,...
2021-JMLR-Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks 2021.6-Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better 2022-IJCAI-Recent Advances on Neural Network Pruning at Initialization Papers [Pruning and...
Recent Advances in Artificial Intelligence 来自 Semantic Scholar 喜欢 0 阅读量: 107 作者: IB Ciocoiu 摘要: The paper focuses on several recent applications of deep learning approaches to a broad range of tasks, including a personal view on current trends, critical issues, and limitations of the ...
Deep learningWindows securityAndroid securityLinux securityMalware analysisneural networksMachine learningMalware datasetMalware is one of the most common and severe cyber threats today. Malware infects millions of devices and can perform several malicious activities including compromising sensitive data, ...
【联邦学习】综述《Advances and Open Problems in Federated Learning》论文结构 该文章由来自麻省理工、斯坦福、加州大学、南阳理工、谷歌等25所国际知名高校(机构)的58位学者联合发表,文章源于2019年6月17日至18日在谷歌西雅图举办的联邦学习学习和分析研讨会,共105页,调研了438篇文献,讲解了最新的联邦学习进展,并提...
Background: Data quality is crucial to the success of big data analytics. However, the presence of outliers affects data quality and data analysis. Employi... M Wang,W Cao,D Hongyan - 《Recent Advances in Computer Science & Communications》 被引量: 0发表: 2024年 Data-Driven Exploration of...
Intelligent computing technology is rapidly developing as artificial intelligence (AI) and big data’s era are coming. In this special issue focused on Recent Development on Intelligent Computing, we shall solicit the survey papers related to pattern rec