Tutorial Object Detection People With Faster Region Based Convolutional Neural Network Faster R Cnn
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Tutorial Object Detection People With Faster region-Based Convolutional Neural Network(Faster R-CNN)
Dalam istilah praktis, deep learning merupakan bagian dari machine learning. Sebuah model machine learning perlu 'diberitahu' untuk bagaimana ia menciptakan prediksi akurat, dengan terus diberikan data. Sementara model deep learning dapat mempelajari metode komputasinya sendiri, dengan 'otaknya' sendiri, apabila diibaratkan. Sebuah model deep learning dirancang untuk terus menganalisis data dengan struktur logika yang mirip dengan bagaimana manusia mengambil keputusan. Untuk dapat mencapai kemampuan itu, deep learning menggunakan struktur algoritma berlapis yang disebut artificial neural network (ANN).
A Guide to Convolutional Neural Networks for Computer Vision
Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs.The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
Digital Transformation
The book offers aspects related to the health and process safety field, complex approaches to artificial intelligence, the role of accounting and auditing in the digital age, DT in agriculture, artificial intelligence in the maritime domain, education, management, sustainability and mobile technologies in learning. Digitization, digitalization and digital transformation (DT) are important for public organizations and private organizations. Despite their importance, these steps are approached differently in organizations. Public organizations emphasize the importance of digital transformation, while public organizations make efforts to align themselves with citizens' demands from a digitalization perspective. Incorporating technologies into organizational processes has become a priority for all industries to lead to important changes. All these activities are covered by the digital transformation that can lead to increased efficiency, agility, innovation and the unlocking of organizational values. Through this complex approach, the book contributes to the completion of knowledge in the field of digital transformation, develops and anticipates new research directions. It is addressed to professionals, practitioners, researchers, students and other interested parties.