The main topic of this volume of the "Journal of Biomimetics, Biomaterials and Biomedical Engineering" is a special textile application in biomedical practice for wound and pressure ulcer prevention and in sport for trauma defence, procuring thermal comfort and monitoring of physical parameters during the training. In this issue, readers also can find research results on the influence of bioactive and bio-inert ceramic powders on tribology properties of polymer matrix composite dentures.

The 45th volume of the "Journal of Biomimetics, Biomaterials and Biomedical Engineering" presents the latest research results in the field of biomechanics and design of foot pressure sensors, and biomimetic foot analyzes, biomechanical analysis of the influence of different surfaces on long-distance running. Also, there is data about biocomposite with glycerol as the dura mater and the study on a novel method to extract hydroxyapatite from the bovine bone without producing hazardous residue. It depicts developing an AI-based computer-aided diagnosis tool using a chest X-ray. This volume will be interesting for researchers in sport science, prothesis and biomaterials.

This volume of the periodical includes papers which describe: - improvement of analysis and measurement methods that are used in the biomedical practice - development and utilization of modern biomaterials and various techniques of diagnosis, therapy and treatment in medicine. We hope that this issue of our journal will be useful for researchers and engineers developing different branches of applied science related to biomedical engineering.

This volume of the "Journal of Biomimetics, Biomaterials and Biomedical Engineering" covers topical issue of biomimetic approach to the development of modern means of a wide range of industrial applications, the new solutions in the field of biomedical engineering and of pharmacological practice and also illuminates the results of the latest solutions in the field of development of biomaterials and their application.

This volume of the "Journal of Biomimetics, Biomaterials and Biomedical Engineering" covers topical issue of biomimetic approach to the development of modern means of a wide range of industrial applications, the new solutions in the field of biomedical engineering and of pharmacological practice and also illuminates the results of the latest solutions in the field of development of biomaterials and their application.

This volume of the "Journal of Biomimetics, Biomaterials and Biomedical Engineering" covers topical issue of biomimetic approach to the development of modern means of a wide range of industrial applications, the new solutions in the field of biomedical engineering and of pharmacological practice and also illuminates the results of the latest solutions in the field of development of biomaterials and their application.

This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3. The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.