A comprehensive survey: Evaluating the efficiency of artificial intelligence and machine learning techniques on cyber security solutions
Given the continually rising frequency of cyberattacks, the adoption of artificial intelligence
methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement …
methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement …
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Dense convolutional network and its application in medical image analysis
T Zhou, XY Ye, HL Lu, X Zheng, S Qiu… - BioMed Research …, 2022 - Wiley Online Library
Dense convolutional network (DenseNet) is a hot topic in deep learning research in recent
years, which has good applications in medical image analysis. In this paper, DenseNet is …
years, which has good applications in medical image analysis. In this paper, DenseNet is …
Real-time data visual monitoring of triboelectric nanogenerators enabled by Deep learning
The rapid advancement of smart sensors and logic algorithms has propelled the widespread
adoption of the Internet of Things (IoT) and expedited the advent of the intelligent era. The …
adoption of the Internet of Things (IoT) and expedited the advent of the intelligent era. The …
Crsf: An intrusion detection framework for industrial internet of things based on pretrained cnn2d-rnn and svm
S Li, G Chai, Y Wang, G Zhou, Z Li, D Yu, R Gao - IEEE Access, 2023 - ieeexplore.ieee.org
The traditional support vector machine (SVM) requires manual feature extraction to improve
classification performance and relies on the expressive power of manually extracted …
classification performance and relies on the expressive power of manually extracted …
Efficient depthwise separable convolution accelerator for classification and UAV object detection
Depthwise separable convolutions (DSC) have been widely deployed in lightweight
convolutional neural networks due to high efficiency. But the acceleration performance of the …
convolutional neural networks due to high efficiency. But the acceleration performance of the …
CoMB-deep: composite deep learning-based pipeline for classifying childhood medulloblastoma and its classes
O Attallah - Frontiers in neuroinformatics, 2021 - frontiersin.org
Childhood medulloblastoma (MB) is a threatening malignant tumor affecting children all over
the globe. It is believed to be the foremost common pediatric brain tumor causing death …
the globe. It is believed to be the foremost common pediatric brain tumor causing death …
Face mask recognition from audio: The MASC database and an overview on the mask challenge
The sudden outbreak of COVID-19 has resulted in tough challenges for the field of
biometrics due to its spread via physical contact, and the regulations of wearing face masks …
biometrics due to its spread via physical contact, and the regulations of wearing face masks …
基于改进YOLOv5s 的安全帽检测算法
赵睿， 刘辉， 刘沛霖， 雷音， 李达 - 北京航空航天大学学报, 2021 - bhxb.buaa.edu.cn
针对现有安全帽检测算法难以检测小目标, 密集目标等缺点, 提出一种基于YOLOv5s
的安全帽检测改进算法. 采用DenseBlock 模块来代替主干网络中的切片结构 …
的安全帽检测改进算法. 采用DenseBlock 模块来代替主干网络中的切片结构 …
Deep Learning-Assisted Intelligent Artificial Vision Platform Based on Dual-Luminescence Eu (III)-Functionalized HOF for the Diagnosis of Breast and Ovarian Cancer
Z Hu, B Yan - Analytical Chemistry, 2023 - ACS Publications
Developing an advanced analytical method to detect spermine (Spm) and N-
acetylneuraminic acid (NANA), the biomarkers of breast and ovarian cancers, respectively …
acetylneuraminic acid (NANA), the biomarkers of breast and ovarian cancers, respectively …