Kirjojen hintavertailu. Mukana 12 152 606 kirjaa ja 12 kauppaa.
Kirja.info

Kirjahaku

Etsi kirjoja tekijän nimen, kirjan nimen tai ISBN:n perusteella.

831 tulosta hakusanalla Sivakumar Rajeshkumar

A Complete Guide to Portals and User Experience Platforms

A Complete Guide to Portals and User Experience Platforms

Shailesh Kumar Shivakumar

Productivity Press
2015
sidottu
Build a Next-Generation Enterprise Digital Platform with Portals and UXPA Complete Guide to Portals and User Experience Platforms provides in-depth coverage of portal technologies and user experience platforms (UXPs), which form the key pillars of a modern digital platform. Drawing on his experience in various roles in numerous portal engagements, the author gives you different perspectives of the same technology platform.The first section introduces portal through multiple viewpoints to cater to a wide audience, including business, operations, development, integration, performance, and architecture views. The book details many novel and practically proven models and frameworks, such as portal value realization framework, portal assessment framework, portal evaluation model, portal infrastructure planning techniques, and portal integration techniques. You also learn about effective digital program strategies, including portal roadmap strategy, collaboration strategy, portal security planning, portal testing strategy, SEO, and analytics planning concepts.The second section dives into UXP and advanced topics. It elaborates on UXP design concepts, including UXP reference architecture, customer touch point analysis, user experience mapping, and responsive web design. It also looks at advanced topics, such as next-generation portals, portal trends, portal user experience strategy, omni-channel strategy, portal KPI, portal pitfalls and best practices, portal security, portal governance, digital program management, and portal performance engineering. In the third section, the book presents four case studies related to intranet portals, retail portals, customer service portals, and portal content management. It discusses business drivers, challenges, portal solutions, and solution benefits for each of the case studies.Written by a seasoned practitioner, this book balances the core topics of modern portals along with emerging technologies in the digital space. Suitable for the entire digital technology community, including IT managers, digital architects, developers, and testers, it provides you with a practical guide for successfully building best practices-based digital platforms with forward-looking features.
Vertaile hintoja
Speech Recognitio on Deep Learning

Speech Recognitio on Deep Learning

A P Siva Kumar; K Durga Akhil; Chidananda K

LAP Lambert Academic Publishing
2021
pokkari
Speech Recognition using Convolution neural network, is used to recognized the words and digitize them and analyze the sound. It trains a deep learning model that detects the presence of speech commands in audio. It uses a convolution neural network to train a model. The model was trained for commands and background noise. The trained model getting accuracy of 96.34% while testing the data. Define the level for audio processing and the level of identification in Hz and build an audio interface viewer that can interpret audio from your micro phone. When we speak commands it detects and visualize it and we speak other than commands it shows unknown. When we not speaking anything it detecting background noise.
Vertaile hintoja
Speech Recognition on Deep Learning

Speech Recognition on Deep Learning

A P Siva Kumar; K Durga Akhil; Chidananda K

LAP Lambert Academic Publishing
2021
pokkari
Speech Recognition using Convolution neural network, is used to recognized the words and digitize them and analyze the sound. It trains a deep learning model that detects the presence of speech commands in audio it implemented by using MATLAB. It uses a convolution neural network to train a model. The model was trained for commands and background noise. The trained model getting accuracy of 96.34% while testing the data. Define the level for audio processing and the level of identification in Hz and build an audio interface viewer that can interpret audio from your microphone. When we speak commands it detects and visualize it and we speak other than commands it shows unknown. When we not speaking anything it detecting background noise.
Vertaile hintoja
Técnica de dropout para Classificação de Imagens

Técnica de dropout para Classificação de Imagens

A P Siva Kumar; Tejaswini K; Chidananda K

International Book Market Service Ltd
2023
pokkari
Uma m quina de aprendizagem extrema (ELM) uma rede neural (FFN) feed-forward. Ela desempenha um papel crucial na classifica o de imagens e um m todo simples de aprendizagem de caracter sticas e a ELM frequentemente utilizada na aprendizagem sequencial, aprendizagem em lote e aprendizagem incremental devido a essas inclina es a ELM est aprendendo mais r pido, velocidade, boa capacidade de generaliza o, facilidade de implementa o e efici ncia nas classifica es. Neste trabalho, propomos dois est gios: o est gio de mapeamento de caracter sticas, est gio de aprendizagem de caracter sticas em uma m quina de aprendizagem extrema.
Vertaile hintoja
1...2021222324...42