Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2021.
(EL)
Machine Learning applications has transformed everyday life as well as industry by
providing new successful opportunities in healthcare, transportation, banking, security,
media monitoring and more. Computer Vision is an application of Machine Learning that
recently has done a lot of progress, particularly in Face Recognition and Object Detection
systems. These systems require large data sets to be trained with. Nevertheless, the
available data sets contain large amounts of unlabelled samples.
Active Learning is an innovative field that addresses the challenge of labelling large
sets of unlabelled samples by leveraging only a small amount of manually labelled data.
An efficient way of labelling a small amount of training data is utilizing user-friendly
annotation tools. The latter allow playing a whole video streaming and capturing the
desired entities. This interactive method could be very efficient as well as time-saving in
comparison to traditional data collection methods.
This thesis builds on state-of-the-art Face Recognition and Object Detection models,
by implementing optimization methods that enhance the recognition accuracy. Further
training is being introduced by making use of a robust Active Learning framework that
results in creating extended data sets. Finally, our thesis proposes an integrated system,
which involves effective techniques of associating face and object identification informa-
tion, in order to extract as much knowledge as possible from a video streaming, in real-time.
(EN)
Submitted by ΧΡΙΣΤΙΝΑ ΤΖΟΓΚΑ (
[email protected]) on 2021-07-07T07:25:18Z
No. of bitstreams: 3
license_rdf: 908 bytes, checksum: 0175ea4a2d4caec4bbcc37e300941108 (MD5)
TzogkaChristinaMsc.pdf: 3634974 bytes, checksum: 3d48f0312a51c2a9a0ac66e0fe53575a (MD5)
TzogkaChristinaMsc2021present.pptx: 3336654 bytes, checksum: fe023dbd04d82c74ccbd2942893cbe57 (MD5)
(EN)
Made available in DSpace on 2021-07-07T12:58:32Z (GMT). No. of bitstreams: 3
license_rdf: 908 bytes, checksum: 0175ea4a2d4caec4bbcc37e300941108 (MD5)
TzogkaChristinaMsc.pdf: 3634974 bytes, checksum: 3d48f0312a51c2a9a0ac66e0fe53575a (MD5)
TzogkaChristinaMsc2021present.pptx: 3336654 bytes, checksum: fe023dbd04d82c74ccbd2942893cbe57 (MD5)
Previous issue date: 2021-06
(EN)
Approved for entry into archive by Κυριακή Μπαλτά (
[email protected]) on 2021-07-07T12:58:32Z (GMT) No. of bitstreams: 3
license_rdf: 908 bytes, checksum: 0175ea4a2d4caec4bbcc37e300941108 (MD5)
TzogkaChristinaMsc.pdf: 3634974 bytes, checksum: 3d48f0312a51c2a9a0ac66e0fe53575a (MD5)
TzogkaChristinaMsc2021present.pptx: 3336654 bytes, checksum: fe023dbd04d82c74ccbd2942893cbe57 (MD5)
(EN)
University of Macedonia
