Using Convolutional Autoencoders to Detect Anomalies in Sewer Images

Kesteloo, M.E. (Mitchell)

LIACS Thesis Repository

These webpages contain theses and reports by students affiliated with the various bachelor and master programmes offered at the Leiden Institute of Advanced Computer Science (LIACS), the computer science and artificial intelligence department of Leiden University.
Note: this thesis repository might be incomplete for certain programmes.

Bachelor Informatica

The following thesis was written by a student in the 2016-2017 class of the Bachelor Informatica programme at Leiden University.

Thesis details

Title	Using Convolutional Autoencoders to Detect Anomalies in Sewer Images
Student	Kesteloo, M.E. (Mitchell)
Programme	Bachelor Informatica
Year	2016-2017
Supervisors	D. Meijer (first supervisor) Knobbe, dr. A.J. (Arno)
Thesis	Open Thesis PDF

Citation details

Kesteloo, M.E. (Mitchell), Using Convolutional Autoencoders to Detect Anomalies in Sewer Images, Thesis Bachelor Informatica, LIACS, Leiden University, 2017.