Neural Style Transfer (NST) is a class of software algorithms that allows us to transform scenes, change/edit the environment of a media with the help of a Neural Network. NST finds use in image and video editing software allowing image stylization based on a general model, unlike traditional methods. This made NST a trending topic in the entertainment industry as professional editors/media producers create media faster and offer the general public recreational use. In this paper, the current progress in Neural Style Transfer with all related aspects such as still images and videos is presented critically. The authors looked at the different architectures used and compared their advantages and limitations. Multiple literature reviews focus on the Neural Style Transfer of images and cover Generative Adversarial Networks (GANs) that generate video. As per the authors' knowledge, this is the only research article that looks at image and video style transfer, particularly mobile devices with high potential usage. This article also reviewed the challenges faced in applying for video neural style transfer in realtime on mobile devices and presents research gaps with future research directions. NST, a fascinating deep learning application, has considerable research and application potential in the coming years.
Soft robotics, an emerging field at the intersection of robotics and materials science, has gained significant attention in recent years due to its potential for creating highly adaptable and versatile robotic systems. Unlike traditional rigid robots, soft robotics focuses on designing and controlling flexible mechatronic systems that can mimic the natural movements and interactions of living organisms. This paper presents an overview of the recent innovations in soft robotics, specifically focusing on the design and control aspects of flexible mechatronic systems.The design of soft robots involves the integration of advanced materials and mechanisms that enable compliance and flexibility in the robot's body structure. Various materials, such as elastomers, hydrogels, and shape-memory polymers, have been explored for constructing soft robotic components that can deform and recover their shape. These materials exhibit unique properties, such as stretchability, elasticity, and self-healing capabilities, allowing soft robots to adapt to complex and dynamic environments. Additionally, the design of soft robotic systems often incorporates pneumatic or hydraulic actuation mechanisms to achieve locomotion and manipulation.In conclusion, this paper provides an overview of the recent innovations in soft robotics, focusing on the design and control of flexible mechatronic systems. Soft robots have the potential to revolutionize various fields by providing adaptive and versatile robotic systems. The integration of advanced materials, novel actuation mechanisms, and innovative control strategies has paved the way for the development of soft robots with remarkable capabilities. However, further research is needed to address the existing challenges and unlock the full potential of soft robotics in practical applications.
Real-time image processing and computer vision techniques have become increasingly important in the field of mechatronic systems. Mechatronic systems integrate mechanical, electrical, and computer engineering to create advanced systems with enhanced functionality and performance. The integration of image processing and computer vision in mechatronic systems has opened up new possibilities for applications such as object detection, tracking, recognition, and robotic vision.This paper aims to provide an overview of the various real-time image processing and computer vision techniques employed in mechatronic systems. It explores the fundamental concepts, methodologies, and algorithms used in these techniques to extract meaningful information from images and videos, enabling mechatronic systems to make intelligent decisions based on visual inputs. The real-time image processing and computer vision techniques play a vital role in mechatronic systems, enabling intelligent decision-making based on visual inputs. This paper provides a comprehensive overview of these techniques, including their fundamental principles, implementation considerations, and practical applications. The advancements in real-time image processing and computer vision continue to push the boundaries of mechatronic systems, unlocking new possibilities and driving innovation in various industries
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