Special Issue "New Trends in Artificial Intelligence and Deep learning for Instrumentation, Sensors, and Robotics"

Submission Deadline: 31 July 2021 (closed)
Guest Editors
Dr. Mohammad Tabrez Quasim, University of Bisha, Saudi Arabia.
Dr. Fahad Algarni, University of Bisha, Saudi Arabia.
Dr. Rihem Farkh, King Saud University, Saudi Arabia.
Dr. Kapal Dev, CONNECT Centre, Trinity Collge Dublin, Ireland.


At present, robotics behaves and moves like human, the next step in robotics is towards enhancing robots to think like human and make instantaneous decisions without any human interventions. In order to accomplish this, machine learning algorithms and intelligent sensors introduced into robotics.
Instrumentation encompasses measurement techniques, statistical analysis of the information from sensor measurements and the associated equipment. Deep learning and Machine Learning have gone through a massive growth in the past several years. In many domains, such as perception, vision, image recognition, image captioning, speech recognition, machine translation, and board games. Artificial Intelligence (AI) in Instrumentation, Sensors and Robotics addresses advanced AI-embedded and secure technologies for modeling, analysis, synthesis, experimentation, deployment of sensor, control, monitoring, and decision systems.

• Artificial Intelligence (AI), Machine Learning and Deep Learning in Instrumentation/ Measurement
• Artificial Intelligence (AI), Machine Learning and Deep Learning in Robotics
• Artificial Intelligence, Machine Learning and Deep Learning in sensors networks
• Big Data analytics for data processing from SNs
• Intelligence image processing algorithms for SNs and Robots
• Clustering and classification algorithms for instrumentation, SNs and robotics

Published Papers
  • Combining CNN and Grad-Cam for COVID-19 Disease Prediction and Visual Explanation
  • Abstract With daily increasing of suspected COVID-19 cases, the likelihood of the virus mutation increases also causing the appearance of virulent variants having a high level of replication. Automatic diagnosis methods of COVID-19 disease are very important in the medical community. An automatic diagnosis could be performed using machine and deep learning techniques to analyze and classify different lung X-ray images. Many research studies proposed automatic methods for detecting and predicting COVID-19 patients based on their clinical data. In the leak of valid X-ray images for patients with COVID-19 datasets, several researchers proposed to use augmentation techniques to bypass this limitation.… More
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  • Medical Image Transmission Using Novel Crypto-Compression Scheme
  • Abstract The transmission of medical records over indiscrete and open networks has caused an increase in fraud involving stealing patients’ information, owing to a lack of security over these links. An individual’s medical documents represent confidential information that demands strict protocols and security, chiefly to protect the individual’s identity. Medical image protection is a technology intended to transmit digital data and medical images securely over public networks. This paper presents some background on the different methods used to provide authentication and protection in medical information security. This work develops a secure cryptography-based medical image reclamation algorithm based on a combination of… More
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  • Main Path Analysis to Filter Unbiased Literature
  • Abstract Citations are references used by researchers to recognize the contributions of researchers in their articles. Citations can be used to discover hidden patterns in the research domain, and can also be used to perform various analyses in data mining. Citation analysis is a quantitative method to identify knowledge dissemination and influence papers in any research area. Citation analysis involves multiple techniques. One of the most commonly used techniques is Main Path Analysis (MPA). According to the specific use of MPA, it has evolved into various variants. Currently, MPA is carried out in different domains, but deep learning in the field… More
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