 |
|
|
Item Details
| Title:
|
DECISION FORESTS
|
| By: |
Antonio Criminisi, Jamie Shotton, Ender Konukoglu |
| Format: |
Paperback |
| List price:
|
£82.50 |
|
We currently do not stock this item, please contact the publisher directly for
further information.
|
|
|
|
|
|
| ISBN 10: |
1601985401 |
| ISBN 13: |
9781601985408 |
| Publisher: |
NOW PUBLISHERS INC |
| Pub. date: |
14 March, 2012 |
| Pages: |
162 |
| Description: |
Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis. |
| Synopsis: |
In recent years decision forests have established themselves as one of the most promising techniques in machine learning, computer vision and medical image analysis. This review is directed at engineers and PhD students who wish to learn the basics of decision forests, as well as more senior researchers who wish to push the state-of-the-art in automated image understanding. The authors present a unified, efficient model of random decision forests, which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis. Such applications have traditionally been addressed by different, supervised or unsupervised machine learning techniques. In contrast, this survey casts diverse tasks such as regression, classification, and semi-supervised learning as instances of the same general decision forest model. The flexibility of the forest framework further extends to tasks such as density estimation, manifold learning, and semi-supervised learning.The unified forest framework allows for the opportunity to implement and optimize the underlying algorithm only once, and then easily adapt it to individual applications with relatively small changes. The theoretical basis and numerous explanatory examples presented in this survey serve as a solid platform upon which to build exciting future research. |
| Illustrations: |
black & white illustrations |
| Publication: |
US |
| Imprint: |
now publishers Inc |
| Returns: |
Returnable |
|
|
|
 |
|
|
|
|
|
Little Worried Caterpillar (PB)
Little Green knows she''s about to make a big change - transformingfrom a caterpillar into a beautiful butterfly. Everyone is VERYexcited! But Little Green is VERY worried. What if being a butterflyisn''t as brilliant as everyone says?Join Little Green as she finds her own path ... with just a littlehelp from her friends.
|
|
All the Things We Carry PB
What can you carry?A pebble? A teddy? A bright red balloon? A painting you''ve made?A hope or a dream?This gorgeous, reassuring picture book celebrates all the preciousthings we can carry, from toys and treasures to love and hope. With comforting rhymes and fabulous illustrations, this is a warmhug of a picture book.
|
|
|
|