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Encrypted Neutral Pattern Analysis and Bio-molecular Recognition Systems

Submission Deadline: 10 December 2021 (closed) View: 17

Guest Editors

Dr. N. Krishnaraj, SRM Institute of Science and Technology, India
Dr. Gyanendra Prasad Joshi, Sejong University, South Korea
Dr. T. Jayasankar, Anna University, India
Dr. K. Shankar, Alagappa University, India


In recent decades, many studies are under process to perfect the Encryption in Bio-Medical Engineering (BME) algorithms to act and decide like a human. The research towards adapting the BME algorithm in many required fields is under for the development of Bio-Manufacturing Neural Processing Networks. The advancement of such Neural Pattern based Image Sensing and Cloud Computing is skyrocketing day by day. However, It is essential to distinguish new capabilities created by Neural Pattern Letters and technologies to rethink cloud systems based on Current Bio-Informatics Recognition schemes. Implanting Neural Imaging in an application can be of many forms, such as breakthrough invention -Deep Learning algorithms can be used. The research towards bridging the gap between the real-time applications and the CE (with deep learning algorithms) can be addressed with high priority. At the current COVID - 19 scenarios, mutual distancing is to be followed so that many people will suffer in this situation so that we can implement Neural Image Reality-based Encryption techniques that will help the human kinds for the next advanced technology creators. The combinational effect of Neural Image Processing, BIO, and virtual reality can be applied in the industrial and medical progress and education field through such a well-prepared technology that can access human interaction and computational function to the next level of Bio-Industrial manufacturing growth.


In the 21st century, biomedical imaging will move beyond testing traditional morphological and metabolic parameters, such as tumor size and glucose metabolism, and validating novel endpoints of pattern imaging that will modify patient care and align with clinical outcomes. As our molecular understanding of the disease evolves, and individualized treatments are offered, imaging must also advance to the molecular level and include a personalized approach to each clinical and clinical science sample. Such modern Trend of Neural Biorecognition system will make progress of research and development in the adaptive field science, which can be led by medical sectors or applicable to engineering domains.


We welcome the manuscript through our special issue, which will focus the encryption mythology for the constrain development of neural pattern imaging and its application letters for the better processing for future Bio Recognition systems.


Collective Intelligence in Neural Pattern Processing Interfaces
Neural Pattern Imaging and Signal Transmissions
Bio-recognition System and Encryption Image Science
Deep Neural Pattern Imaging for Identification, Classification, and Segmentation of Medical Images
Deep Neural Pattern Imaging for Diagnosis of Human Brain Condition Disorders
To Detect Tumors, Deep Neural Networks and Encrypted Pattern Processing
Bio-Encrypted Autonomic and Evolutionary Communication
Bio-Inspired and Encrypted Adaptive Industrial Applications
Real Application Experience in Biomedical Imaging Use of Deep Neural Encrypted Pattern Networks
Usage of Deep Neural Networks, including Images, Over Mixed Medical Evidence
Improve Diagnosis and Classification by Deep Neural Pattern Networks
The Development of Conventional Methods of Diagnosis via Deep Neural Pattern Networks
CE Security, Trust, Assurance, and Resilience in Mobile Platforms
Collision-based Intelligence in Neural Pattern Communication
Context-aware Biomedical Networking
Data Aggregation and Fusion of Encrypted Neural Science
Energy-efficient Neural Imaging Monitoring and Processing
Machine Intelligence and Virtual Image Reality
Neuron and Haptic Technology
Neural Network Technology and BIO-Encryption Processing
Augmented Neural Reality and Cyber Space Encryption
Bio-Recognition and Neural Based Pattern Applications

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