Xiaofeng li (601 résultats)

Paperback. Etat : Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Etat : New.

Hardcover. Quarto. Hardcover. Green cloth spine over illustrated boards with white titles. 264 pages : illustrations (chiefly color) ; 29 cm. "The first publication to explore Philadelphia Museum of Art's wide-ranging collection of Chinese art, offering an introduction to general readers and serving as a valuable resource for future research and scholarship. This catalogue of one hundred highlights, drawn from a collection of more than seven thousand objects spanning more than four thousand years, will be both a sumptuous visual record of the Philadelphia Museum of Art's most notable Chinese works and an informative and valuable reference for those interested in Chinese art. The objects have been selected to show not only the strengths of the collection, but also important and distinctive examples of Chinese art in different mediums. They are also intended to bring together the museum's Chinese collection, which is presently housed in such disparate departments as Chinese export art, costume and textiles, Sino-Tibetan art, and contemporary art--representing sculpture, ceramics, furniture, architectural interiors, textiles, and paintings"--. G+. Small bookplate inside front cover. Damp staining to spine and light water damage at base of spine that does not affect readability.…

Etat : As New. New and sealed.

Etat : As New. Brand new, in original shrink wrap.

XIX, 255 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Paperback. Etat : new. Paperback. This open access book invites readers to learn how to develop artificial intelligence (AI)-based algorithms to perform their research in oceanography. Various examples are exhibited to guide details of how to feed the big ocean data into the AI models to analyze and achieve optimized results. The number of scholars engaged in AI oceanography research will increase exponentially in the next decade. Therefore, this book will serve as a benchmark providing insights for scholars and graduate students interested in oceanography, computer science, and remote sensing. This open access book invites readers to learn how to develop artificial intelligence (AI)-based algorithms to perform their research in oceanography. Therefore, this book will serve as a benchmark providing insights for scholars and graduate students interested in oceanography, computer science, and remote sensing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Etat : Brand New. 43 pages. 6.00x0.10x9.00 inches. In Stock.

hardcover. Etat : New. New. Clean, unmarked pages. Fine binding and cover. Hardcover, in shrink wrap. This is an oversized or heavy book, which requires additional postage for international delivery outside the US.

Etat : New.

Paperback. Etat : Brand New. 358 pages. 9.25x6.10x9.25 inches. In Stock.

Paperback or Softback. Etat : New. Big Scientific Data Management: First International Conference, Bigsdm 2018, Beijing, China, November 30 - December 1, 2018, Revised Selected Papers. Book.

Etat : New.

Etat : New.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New.

Etat : Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : New. Print on Demand.

Paperback. Etat : New. 2022 ed. This book provides a thorough overview of the evolution of privacy-preserving machine learning schemes over the last ten years, after discussing the importance of privacy-preserving techniques. In response to the diversity of Internet services, data services based on machine learning are now available for various applications, including risk assessment and image recognition. In light of open access to datasets and not fully trusted environments, machine learning-based applications face enormous security and privacy risks. In turn, it presents studies conducted to address privacy issues and a series of proposed solutions for ensuring privacy protection in machine learning tasks involving multiple parties. In closing, the book reviews state-of-the-art privacy-preserving techniques and examines the security threats they face.…

Etat : New. pp. 362.

Etat : New. pp. 362.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.