Internet of Things (IoT) is the rapidly growing domain that facilitates seamless connectivity to physical objects that makes them suitable and ideal entity of smart environment. The enforcement of trust between the physical objects is essential for completely utilizing the significant potentiality of these connected IoT objects. The traditional security strategies are not potent enough in provisioning comprehensive protection to the smart world. In this paper, Bipolar Fuzzy PROMETHEE-based Decision-Making Trust Model (BFPSMTM) is
Image and video processing research is becoming an important area in the field of computer vision. There are challenges such as low-resolution images, poor quality of videos, etc. in image and video data processing. Deep learning is a machine learning technique used in the creation of AI systems. It is designed to analyse complex data by passing it through many layers of neurons. Deep learning techniques have the potential to produce cutting-edge results in difficult computer vision problems such as object identification and face recognition. In this chapter, the use of deep learning to target specific functionality in the field of computer vision such as image recovery, video classification, etc. The deep learning algorithms, such as convolutional neural networks, deep neural network, and recurrent neural networks, used in the image and video processing domain are also explored.
Sign language facilitates communication in the community with speaking and hearing problems. Those people communicate with one another using hand gestures and body movements. These techniques of human-computer interaction range from primary keyboard inputs to complex vision-based gesture detection systems. One of the fascinating HCI technologies is hand gesture recognition. The goal of gesture recognition is to construct a system to use as a communication medium in various applications. The application of gesture recognition has become popular in healthcare, robotics, etc. Posture recognition is deployed in several sectors, including medicine. Deep learning-based models are used to understand gesture and posture recognition results better. This chapter covers the challenges of gesture and posture recognition and how deep learning techniques are used to assist machines in overcoming these challenges more effectively. In addition, this chapter also discusses the applications in which gesture and posture recognition can be employed in detail.
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