... The framework combines mobile-fog-cloud architecture with blockchain-enabled DRL to address data security, resource allocation and workflow management. It uses deep learning and blockchain for data validation and secure transactions, supported by a symmetric cryptographic scheme for smart contracts...

...Dongfang Lv; Xiaotong Wei; Dazhou Li; Han Xu; Xin Chen; Guangjie Han Purpose This paper aims to develop a novel deep learning model integrating the Internet of Medical Things (IoMT) for cell detection in biomedical images. Given the significance of real-time acquisition and processing of vast...

... defect – prediction models. Corresponding author Sihan Chen sihanchen@csu.edu.cn 27 05 2025 17 06 2025 17 06 2025 © 2025 Emerald Publishing Limited 2025 Emerald Publishing Limited Licensed re-use rights only Deep learning Machine learning Feature selection Web...

... limitations in exercise difficulty assessment by introducing a multi-concept fusion mechanism for comprehensive KT. This paper proposes AuBoKT, a deep learning framework leveraging auxiliary features to model fine-grained student interactions while dynamically integrating educational forgetting/learning...

...Shahad Thamear Ameen; Salman Yussof; Azhana Ahmad; Saif Khadim; Ahmed Hussain Purpose The purpose of this paper is to introduce a novel deep learning model for translating sign language in the Web-based e learning platforms. The increased utilization of Web-based e-learning systems highlighted...

... Publishing Limited 2024 Emerald Publishing Limited Licensed re-use rights only Crowdsourcing Task recommendation Deep learning Imbalance data Title: A concise introduction to the task. Skill requirements: The skills that the task publisher expects workers who can complete the task...

... defect prediction (SDP), researchers often use deep learning techniques to extract various features from the source code of software, thus improving the accuracy of defect prediction models (Croft et al., 2022 ; Chen and Wang, 2022 ; Xie and Jianhua, 2024 ; Meng et al., 2023a...

...Feng Qian; Yongsheng Tu; Chenyu Hou; Bin Cao Purpose Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed...

... it challenging for ViT to perform well on smaller data sets (Liu et al., 2021). Indeed, larger deep learning models inherently offer some advantages due to their generalization capabilities. Consistent with this idea, researchers have proposed various multi-model methods for RSI classification...

...Yong Ding; Peixiong Huang; Hai Liang; Fang Yuan; Huiyong Wang Purpose Recently, deep learning (DL) has been widely applied in various aspects of human endeavors. However, studies have shown that DL models may also be a primary cause of data leakage, which raises new data privacy concerns...

... and tracking of people related to crime prevention. This paper provides exhaustive comparison between the existing methods and proposed method. Proposed method is found to have highest object detection accuracy. Design/methodology/approach The goal of this research is to develop a deep learning framework...

...Ibtehal Talal Nafea Purpose This study aims to propose a new simulation approach for a real-life large and complex crowd management which takes into account deep learning algorithm. Moreover, the proposed model also determines the crowd level and also sends an alarm to avoid the crowd from...