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97,604 result(s) for "Artificial intelligence Computer networks."
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Strengthening deep neural networks : making AI less susceptible to adversarial trickery
\"As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately \"fool\" them with data that wouldn't trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs--the algorithms intrinsic to much of AI--are used daily to process image, audio, and video data. -- Provided by publisher.
Counseling (ro)bot as a use case for 5G/6G
This paper presents a counseling (ro)bot called Visual Counseling Agent (VICA) which focuses on remote mental healthcare. It is an agent system leveraging artificial intelligence (AI) to aid mentally distressed persons through speech conversation. The system terminals are connected to servers by the Internet exploiting Cloud-nativeness, so that anyone who has any type of terminal can use it from anywhere. Despite a promising voice communication interface, VICA shows limitations in conversation continuity on conventional 4G networks. Concretely, the use of the current 4G networks produces word dropping, delayed response, and the occasional connection failure. The objective of this paper is to mitigate these issues by leveraging a 5G/6G slice inclusive of mobile/multiple edge computing (MEC). First, we propose and partly implement the enhanced and advanced version of VICA. Servers of enhanced versions collaborate to increase speech recognition reliability. Although it significantly increases generated data volume, the advanced version enables a recognition of the facial expressions to greatly enhance counseling quality. Then, we propose a quality assurance mechanism using multiple levels of catalog, as well as 5G/6G slice inclusive of MEC, and conduct experiments to uncover issues related to the 4G. Results indicate that the number of speech recognition errors in Internet Cloud is more than twofold compared to edge computing, implying that quality assurance using 5G/6G in conjunction with VICA Counseling (ro)bot has higher efficiency.
Advanced deep learning with TensorFlow 2 and Keras : apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more
A second edition of the bestselling guide to exploring and mastering deep learning with Keras, updated to include TensorFlow 2.x with new chapters on object detection, semantic segmentation, and unsupervised learning using mutual information.
Intelligent network management and control : intelligent security, multi-criteria optimization, cloud computing, internet of vehicles, intelligent radio
The management and control of networks can no longer be envisaged without the introduction of artificial intelligence at all stages. 'Intelligent Network Management and Control' deals with topical issues related mainly to intelligent security of computer networks, deployment of security services in SDN (software-defined networking), optimization of networks using artificial intelligence techniques and multi-criteria optimization methods for selecting networks in a heterogeneous environment.
Introduction to EEG- and speech-based emotion recognition
Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using electroencephalograms (EEGs) to detect and recognize different emotions.By incorporating these methods in brain-computer interface (BCI), we can achieve more natural, efficient communication between humans and computers.
Deep learning for computer vision
Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision, the science of manipulating and processing images. In this book, you will learn different techniques in deep learning to accomplish tasks related to object classification, object detection, image segmentation, captioning, ...