DEEP LEARNING FOR COMPUTER VISION

· · ·
· Xoffencerpublication
Электронная кніга
220
Старонкі
Ацэнкі і водгукі не спраўджаны  Даведацца больш

Пра гэту электронную кнігу

In the most recent few years, tremendous technical progress has been made in the creation of high-throughput graphics processing units in addition to parallel processing. Processing in parallel has allowed for the realisation of these recent advancements. (GPUs). The amount of computational power that is now accessible has significantly risen, yet the needed amount of power consumption has stayed the same. Highperformance parallel processing units are now accessible at a price that is affordable for almost everyone. This is because many of these systems are developed for the consumer market to deliver high-definition gaming experiences. Although they have been considerably altered to make graphical calculations more effective, they are broad enough to be utilised in a range of different jobs that may be completed concurrently. This is despite the fact that they have been adjusted to make graphical calculations more effective. This new advancement will have a tremendous impact on the whole area of study that focuses on deep learning. At this point in time, it is feasible for anybody to use the most recent techniques of deep learning to their work, regardless of whether they are doing their study in conventional laboratories or at home. Deep learning is a subfield of machine learning that has shown its usefulness for a variety of activities that are deemed simple for humans but too tough for computers to handle on their own. Image recognition, natural language processing, and voice recognition are all examples of the tasks that fall under this category. Natural language processing and image analysis are two examples of this kind of technology. Both of these include the categorization, identification, and segmentation of various items inside pictures. This paves the way for the development of autonomous systems, which in turn paves the way for an infinite number of additional possibilities.

Звесткі пра аўтара

Mr. Amol Dattatray Dhaygude is renowned professional in field of Machine Learning, Artificial Intelligence, Data Science and Computer Science. He is alumni of University of Washington, Seattle, USA with Master of Science in Data Science and specialization in Machine Learning. Amol has 16 years of software industry experience in top tier organizations including IBM, Cognizant and Microsoft Corporation. He is currently employed at Microsoft Corporation for last 10 years in role of Senior Data & Applied Lead at Redmond, Washington. He is inspired to make use of cutting edge technological advancements in field of Machine Learning and Artificial Intelligence to solve real world practical problems making a difference to world. He has strong techno business acumen to formulate and solve business problems with applications of Data Science, Machine Learning and Artificial Intelligence. He is well versed in Deep Learning, Natural Language Processing, and Computer Vision fields of Artificial Intelligence. Amol celebrates growth mindset with continuous learning, embracing challenges, experimentation, fail fast, feedback and continuous improvement principles. He believes in learning from community and at the same time giving back to community by sharing his knowledge through various avenues such as research publications, blogs, patent publications, book publishing etc. Amol has continuously served as editor for books and journals in his areas of expertise.  

Dr. Pushpendra Kumar Verma, is an Associate Professor, School of Computer Science and Applications, IIMT University, Meerut, UP, India. He has done MCA, MTech-CSE. MPhil (CS) and Doctorate in Computer Science. His area of research is in Cryptography and Network and Security/Cyber Security, and his other areas of specialization include Artificial Intelligence and Machine Learning. He has Convener, Keynote Speakers and participated in several high-profile conferences, seminars and workshops. The author has many research papers in international journals, review articles in various Scopus Indexed Journals, international journals and interested in academics and research. He has !7+years extensive teaching and research experience in various Universities as well as colleges across India. He also reviewed the Reputed International Journal Papers. He is member of Vidwan, Springer, International Association of Engineers (IAENG),Society of Digital Information and Wireless Communications (SDIWC) etc. 

Dr. Sheshang D. Degadwala is presently working as Associate Professor and Head of Computer Engineering Department, Sigma University , Vadodara. He has published 235 research papers in reputed international journals and conferences including IEEE, Elsevier and Springer. His main research work focuses on Image Processing, Computer Vision, Information Security, Theory of Computation and Data Mining. He is also Microsoft Certified in Python Programming and Excel. He has published 18 books and he got grant for 3 patents. He has published 125 Indian Patent. He has received 50 awards for academic and research achievement. 

Renato Racelis Maaliw III is an Associate Professor and currently the Dean of the College of Engineering in Southern Luzon State University, Lucban, Quezon, Philippines. He has a doctorate degree in Information Technology with specialization in Machine Learning, a Master's degree in Information Technology with specialization in Web Technologies, and a Bachelor’s degree in Computer Engineering. His area of interest is in artificial intelligence, computer engineering, web technologies, software engineering, data mining, machine learning, and analytics. He has published original researches, a multiple time best paper awardee for various IEEE sanctioned conferences; served as technical program committee for world-class conferences, author, editor and peer reviewer for reputable high-impact research journals. 

Ацаніце гэту электронную кнігу

Падзяліцеся сваімі меркаваннямі.

Чытанне інфармацыb

Смартфоны і планшэты
Усталюйце праграму "Кнігі Google Play" для Android і iPad/iPhone. Яна аўтаматычна сінхранізуецца з вашым уліковым запісам і дазваляе чытаць у інтэрнэце або па-за сеткай, дзе б вы ні былі.
Ноўтбукі і камп’ютары
У вэб-браўзеры камп’ютара можна слухаць аўдыякнігі, купленыя ў Google Play.
Электронныя кнiгi i iншыя прылады
Каб чытаць на такіх прыладах для электронных кніг, як, напрыклад, Kobo, трэба спампаваць файл і перанесці яго на сваю прыладу. Выканайце падрабязныя інструкцыі, прыведзеныя ў Даведачным цэнтры, каб перанесці файлы на прылады, якія падтрымліваюцца.