LEADER 04092nam 2200517 450 001 9910466419003321 005 20200520144314.0 010 $a1-5231-1675-7 010 $a1-78829-335-5 035 $a(CKB)3840000000373031 035 $a(MiAaPQ)EBC5254596 035 $a(WaSeSS)IndRDA00116074 035 $a(CaSebORM)9781788295628 035 $a(PPN)233405208 035 $a(Au-PeEL)EBL5254596 035 $a(CaPaEBR)ebr11505148 035 $a(OCoLC)1022793819 035 $a(EXLCZ)993840000000373031 100 $a20180223h20182018 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aDeep learning for computer vision $eexpert techniques to train advanced neural networks using TensorFlow and Keras /$fRajalingappaa Shanmugamani 205 $a1st edition 210 1$aBirmingham, England :$cPaths International Ltd,$d2018. 210 4$dİ2018 215 $a1 online resource (290 pages) $cillustrations 300 $aIncludes index. 311 $a1-78829-562-5 330 $aLearn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python?and some understanding of machine learning concepts?is required to get the best out of this book. What You Will Learn Set up an environment for deep learning with Python, TensorFlow, and Keras Define and train a model for image and video classification Use features from a pre-trained Convolutional Neural Network model for image retrieval Understand and implement object detection using the real-world Pedestrian Detection scenario Learn about various problems in image captioning and how to overcome them by training images and text together Implement similarity matching and train a model for face recognition Understand the concept of generative models and use them for image generation Deploy your deep learning models and optimize them for high performance In Detail Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. Style and approach This book will teach advanced techniques for Computer Vision, applying the deep learning model in reference to various datasets. Downloading the example code for this... 606 $aArtificial intelligence$xResearch 606 $aNeural networks (Computer science) 608 $aElectronic books. 615 0$aArtificial intelligence$xResearch. 615 0$aNeural networks (Computer science) 676 $a006.3 700 $aShanmugamani$b Rajalingappaa$0869175 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910466419003321 996 $aDeep learning for computer vision$91940577 997 $aUNINA