Transfer learning: a friendly introduction
Infinite numbers of real-world applications use Machine Learning (ML) techniques to
develop potentially the best data available for the users. Transfer learning (TL), one of the …
develop potentially the best data available for the users. Transfer learning (TL), one of the …
A survey and analysis of intrusion detection models based on cse-cic-ids2018 big data
JL Leevy, TM Khoshgoftaar - Journal of Big Data, 2020 - Springer
The exponential growth in computer networks and network applications worldwide has been
matched by a surge in cyberattacks. For this reason, datasets such as CSE-CIC-IDS2018 …
matched by a surge in cyberattacks. For this reason, datasets such as CSE-CIC-IDS2018 …
Deep learning models for real-time human activity recognition with smartphones
With the widespread application of mobile edge computing (MEC), MEC is serving as a
bridge to narrow the gaps between medical staff and patients. Relatedly, MEC is also …
bridge to narrow the gaps between medical staff and patients. Relatedly, MEC is also …
Faster R-CNN for multi-class fruit detection using a robotic vision system
An accurate and real-time image based multi-class fruit detection system is important for
facilitating higher level smart farm tasks such as yield mapping and robotic harvesting …
facilitating higher level smart farm tasks such as yield mapping and robotic harvesting …
Cognitive computing and wireless communications on the edge for healthcare service robots
In recent years, we have witnessed dramatic developments of mobile healthcare robots,
which enjoy many advantages over their human counterparts. Previous communication …
which enjoy many advantages over their human counterparts. Previous communication …
Intelligent fusion-assisted skin lesion localization and classification for smart healthcare
With the rapid development of information technology, the conception of smart healthcare
has progressively come to the fore. Smart healthcare utilizes next-generation technologies …
has progressively come to the fore. Smart healthcare utilizes next-generation technologies …
Global and local feature reconstruction for medical image segmentation
Learning how to capture long-range dependencies and restore spatial information of down-
sampled feature maps are the basis of the encoder-decoder structure networks in medical …
sampled feature maps are the basis of the encoder-decoder structure networks in medical …
EACMS: Emergency access control management system for personal health record based on blockchain
Personal health records (PHRs) are private and vital assets for every patient. There have
been introduced many works on various aspects of managing and organizing the PHR so …
been introduced many works on various aspects of managing and organizing the PHR so …
A CNN-LSTM hybrid model for wrist kinematics estimation using surface electromyography
Convolutional neural network (CNN) has been widely exploited for simultaneous and
proportional myoelectric control due to its capability of deriving informative, representative …
proportional myoelectric control due to its capability of deriving informative, representative …
Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological …
Abstract Computer-aided Invasive Ductal Carcinoma (IDC) grading classification systems
based on deep learning have shown that deep learning may achieve reliable accuracy in …
based on deep learning have shown that deep learning may achieve reliable accuracy in …