Nettsider med emneord «Machine Learning»

Publisert 2. mai 2019 10:33
Publisert 2. mai 2019 10:32
Publisert 11. apr. 2019 15:19

João Gama, Associate Professor at the University of Porto, talks about the limitations of current machine learning and data mining algorithms in dealing with real-time data.

Publisert 5. mars 2019 07:08

Tuyen Trung Truong talks about the gradient descent method, and why such a simple method performs so well in practice.

Publisert 9. feb. 2019 14:42
Publisert 6. feb. 2019 13:49
Publisert 6. feb. 2019 11:21
Publisert 5. feb. 2019 13:12
Publisert 31. jan. 2019 09:54

Christos Dimitrakakis talks about the challenge of identity protection.

Publisert 25. jan. 2019 08:56

Water flow on, in and under glaciers still remains a poorly understood system. Water can flow over the surface of glaciers, as well as through channels inside and under the ice. The water thereby has strong influence both on ice melt and glacier dynamics, making glacial hydrology an important field of study.

Publisert 25. jan. 2019 08:55

Water flow on, in and under glaciers still remains a poorly understood system. Water can flow over the surface of glaciers, as well as through channels inside and under the ice. The water thereby has strong influence both on ice melt and glacier dynamics, making glacial hydrology an important field of study.

Publisert 12. nov. 2018 13:23
Publisert 8. nov. 2018 11:09
Publisert 18. okt. 2018 15:52
Publisert 18. okt. 2018 13:59
Publisert 17. okt. 2018 13:45
Publisert 24. sep. 2018 10:40
Publisert 23. sep. 2018 08:44

The SANT project will be presented at the Cutting Edge Festival.

Publisert 17. sep. 2018 15:34
Publisert 7. sep. 2018 08:46

Lidar point clouds provide excellent and quite accurate points in space, including the quite large rooms of factories or ships. Although they are much more accurate than point clouds derived by other means such as regular cameras or structure light systems, the problem remains that it is really difficult to correctly guess and reconstruct the surfaces from which these points have been sampled. It is typical to first guess and construct meshes from the point clouds, giving a potentially quite uneven structure where a flat wall or round pillar is supposed to be. Guessing whether such unevenness is true or an artifact of an inaccuracy is not impossible because there is a branch of computer vision called photogrammetry, which estimates surface curvature from color gradients. However, this still leaves the problem of cleanly terminating every surface by its edges, which may be sharp, rounded or ragged. Edge detection for sharp edges can be implemented by a well-known computer vision algorithm called the Hough Transform. By putting all these pieces together, a human can receive a lot of help in creating a CAD model from some images and a point cloud.  

Publisert 29. aug. 2018 16:25
Publisert 7. aug. 2018 14:17

The MIREX competition (Music Information Retrieval Evaluation eXchange) is an annual competition targeting challenging machine learning tasks related to music. You may choose one of the MIREX challenges as your Master's thesis project.