...Arash Heidari; Nima Jafari; Sherali Zeadally Purpose Today, anomaly detection is an important area studied across various fields to recognize unusual observations. This paper aims to explore the role of deep learning ( DL ) in developing effective anomaly detection systems (ADSs). Design...

...Yijun Liu; Ruipeng Liu; Zebin He; Jieyan Zhang; Pengfei Chen Purpose This study aims to develop a lightweight, dual-modal deep learning model for accurate classification of water leakage in cable tunnels. By integrating visible and infrared image fusion with a multi-scale global feature extraction...

... a deep learning framework for anomaly detection and damage localization in cable tunnels using vibration signals. The authors propose an adaptive CEEMDAN-wavelet denoising ( ACWD ) algorithm to effectively remove noise and improve signal quality. In addition, a partial-whole double sliding window ( PWDSW...

...Santosh Kumar B.; Krishna Kumar E. Purpose Deep learning techniques are unavoidable in a variety of domains such as health care, computer vision, cyber-security and so on. These algorithms demand high data transfers but require bottlenecks in achieving the high speed and low latency...

... bots may form to launch a DDoS attack, steal confidential data of patients and disrupt the service, and hence detecting this army of bots is paramount. This study aims to detect botnet attacks in health IoT devices using the deep learning technique. Design/methodology/approach This paper focuses...

.... With the experimental analysis, it is noted and observed that the proposed system was able to detect the wall cracks, search the flat surface by the result of no cracks found and it is successful in dealing with the two phases of operation, namely, classification and segmentation with the deep learning technique...

... to complexities associated with the images captured by satellites. Accurate image classification is highly essential in remote sensing applications. However, existing machine learning and deep learning–based classification methods could not provide desired accuracy. The purpose of this paper is to classify...

... of the key challenges where different aspects are extracted from online user-generated content. This study focuses on customer tweets/reviews on different mobile products which is an important form of opinionated content by looking at different aspects. Different deep learning techniques are used...

...-temporal techniques, computer vision and deep learning techniques. Design/methodology/approach Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to Advanced Driver Assistance Systems (ADAS). The core objective of these systems is to cut down...

... and decoders to attain better energy optimization. Ubiquitous machine learning computational model process performs training in a better way than regular supervised learning or unsupervised learning computational models with deep learning techniques, resulting in better learning and optimization...

... due to fast imaging time and low cost. The purpose of this study is to use deep learning technique for automatic detection of COVID-19 using chest x-rays. Design/methodology/approach The authors used a data set containing confirmed COVID-19 positive, common bacterial pneumonia and healthy cases...

... were taken. The first data set has 1427 X-ray images of Covid-19 patients and second data set has 224 images of Covid-19 patients and has classified it using deep learning method and obtained an accuracy of 96.78%. Deep learning Drone Social distancing Covid19 Novel corona virus Drone unit...