Hassan Ugail – författare
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6 produkter
6 produkter
759 kr
Skickas inom 10-15 vardagar
Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning has shown the power of artificial deep neural networks in solving real world visual computing problems with super-human accuracy. The introduction of deep learning into the field of visual computing has meant to be the death of most of the traditional image processing and computer vision techniques. Today, deep learning is considered to be the most powerful, accurate, efficient and effective method with the potential to solve many of the most challenging problems in visual computing.This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine learning. It introduces readers to the world of deep neural network architectures with easy-to-understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find it a handy guide for designing and implementing their own projects in the field of visual computing.
827 kr
Skickas inom 10-15 vardagar
Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning has shown the power of artificial deep neural networks in solving real world visual computing problems with super-human accuracy. The introduction of deep learning into the field of visual computing has meant to be the death of most of the traditional image processing and computer vision techniques. Today, deep learning is considered to be the most powerful, accurate, efficient and effective method with the potential to solve many of the most challenging problems in visual computing.This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine learning. It introduces readers to the world of deep neural network architectures with easy-to-understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find it a handy guide for designing and implementing their own projects in the field of visual computing.
553 kr
Skickas inom 10-15 vardagar
The subject of Partial Differential Equations (PDEs) which first emerged in the 18th century holds an exciting and special position in the applications relating to the mathematical modelling of physical phenomena.
553 kr
Skickas inom 10-15 vardagar
The subject of Partial Differential Equations (PDEs) which first emerged in the 18th century holds an exciting and special position in the applications relating to the mathematical modelling of physical phenomena. The subject of PDEs has been developed by major names in Applied Mathematics such as Euler, Legendre, Laplace and Fourier and has applications to each and every physical phenomenon known to us e.g. fluid flow, elasticity, electricity and magnetism, weather forecasting and financial modelling. This book introduces the recent developments of PDEs in the field of Geometric Design particularly for computer based design and analysis involving the geometry of physical objects. Starting from the basic theory through to the discussion of practical applications the book describes how PDEs can be used in the area of Computer Aided Design and Simulation Based Design. Extensive examples with real life applications of PDEs in the area of Geometric Design are discussed in the book.
554 kr
Skickas inom 10-15 vardagar
By way of applications, they discuss how genuine and non-genuine smiles can be inferred, how gender is encoded in a smile and how it is possible to use the dynamics of a smile itself as a biometric feature.It is often said that the face is a window to the soul.
Artificial Intelligence Assisted Analytical Attribution of Ceramic Art Decoration
Evaluating AI for Identifying William Billingsley’s Works and Some of his Contemporaries
Inbunden, Engelska, 2026
2 902 kr
Kommande
This book reviews the information provided by an artificial intelligence–based methodology for the characterization of artworks and the attribution of a piece to a particular artist. Until now, such approaches have been applied mainly to oil paintings, where supporting scientific evidence from underlying layers is available through IR and X‑ray imaging, as well as chemical analysis of pigments, binders, and resins.The new approach explored in this book adapts these methods to ceramic decoration and the special pigments used for that purpose, which must withstand kiln‑firing temperatures of up to 1000 °C. As with oil paintings, the artistry of ceramic decorators has traditionally been assessed by art experts and connoisseurs, who have not previously had the advantage of considering associated scientific evidence and have therefore relied primarily on stylistic judgment.This volume addresses that gap by focusing specifically on the work of the esteemed ceramic artist William Billingsley, who painted on porcelain from several manufactories, beginning with Derby and later including his own at Nantgarw, during the last two decades of the 18th century and the first two decades of the 19th century. Many examples of Billingsley’s artwork now reside in major museum collections worldwide.The principle remains the same: the artificial intelligence procedure requires training a computer to recognize Billingsley’s verified works and then examine other pieces attributed to him to assess the correctness of their attribution, while also comparing his work to that of contemporaries such as Moses Webster, William Pegg, and Leonard Lead.