nayyar ashish (52 risultati)

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Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Demand for energy is growing day by day in the world. Due to limited resources and continuously growing demand there is an urgent need to utilize our finite resources carefully for a sustainable future. Our common goal is to achieve this task in the most efficient, cost effective, and least polluting manner. The energy available in the exhaust of many energy conversion devices goes as waste, if not utilized properly. Since exhaust gases of an internal combustion engine (ICE) carries away -about 30% of the heat of combustion, it represents a great potential to recover the conserve energy. In this project an energy conservation technology ¿waste heat recovery¿ is used. In this experimental work a waste heat operated counter flow type heat exchanger is developed to utilize the waste heat from the engine exhaust for heating. After developing the heat exchanger, experimental investigation is carried out for effectiveness of heat exchanger, effect on exhaust emissions and performance of the engine when heat exchanger is integrated with engine.

Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 288 | Sprache: Englisch | Produktart: Bücher | With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges. The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking.· Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.

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Taschenbuch. Condizione: Neu. Object Tracking Technology | Trends, Challenges and Applications | Ashish Kumar (u. a.) | Taschenbuch | Contributions to Environmental Sciences & Innovative Business Technology | xiv | Englisch | 2024 | Springer | EAN 9789819932900 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges.The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking. Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.

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Condizione: New. pp. 288.

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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges.The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking. Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.

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Hardcover. Condizione: Brand New. 288 pages. 9.25x6.10x0.69 inches. In Stock.

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PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar ChandanChandan Kumar is pursuing his PhD from the Department of Mechanical Engineering, Rajasthan Technical University Kota, India. He is currently working as an Assistant Professor in the Department of Mechanical Engineering, .

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bhadu JagdishMr. Jagdish Bhadu was born on Sept. 20, 1988. He graduated in Mechanical Engineering from University of Rajasthan, Jaipur (India) in 2009 and joined as lecturer. Mr. Bhadu did M. Tech. Degree in 2015 from Raja.

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Diesel engines are playing a vital role in the field of transportation and power generation. In the present world, much research is going on in the field of renewable energy to replace conventional sources of energy. But it is not very easy to replace diese.