Semi supervised Clustering with Regional Data Objects

Dinler, Derya
Tural, Mustafa Kemal


Semi-supervised iterative teacher-student learning for monocular depth estimation
Süvari, Cemal Barışkan; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2021-2-18)
Advances in robotics area and autonomous vehicles have increased the need for accurate depth measurements. Depth estimation is one of the oldest problems of computer vision area. While the depth can be estimated by using many methods, finding a cheap and efficient way of doing it was studied for many years. Although, depth measurements using Lidar sensors or RGB-D cameras provides accurate results, due to cost and narrow applicability they are not very effective. On the other hand, using deep learning archi...
Semi-parametric Estimation of Count Time Series
Ghahramani, Melody; Dag, Osman; de Leon, Alexander R. (2014-06-27)
A flexible semi-parametric model for autocorrelated count data is proposed. Unlike earlier models available in the literature, the model does not require construction of a likelihood function and only entails the specification of the first two conditional moments. An estimating function approach is adopted for the model. The efficiency of the estimates is investigated numerically against competing estimates via simulation studies.
Semi-supervised dimension reduction approaches integrating global and local pattern information
Sakarya, Ufuk (Springer Science and Business Media LLC, 2019-02-01)
Dimension reduction is an important research area in pattern recognition. Use of both supervised and unsupervised data can be an advantage in the case of lack of labeled training data. Moreover, use of both global and local pattern information can contribute classification performances. Therefore, four important primary components are essential to design a well-performed semi-supervised dimension reduction approach: global pattern modeling by a supervised manner, local pattern modeling by a supervised manne...
Semi-automatic ground-truth trajectory extraction on image sequences
Karabıyık, Murat; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2017)
In this thesis, offline semi-automatic ground-truth trajectory extraction technique is proposed that uses measurements of detector as basis. The unknown camera motion of the videos used throughout the thesis makes the problem even more challenging. The camera motion is estimated by using a novel method which uses a special Kalman filter. Background objects are discriminated from the targets and they are used to estimate the camera motion. Two different trackers are implemented to extract the ground-truth. M...
Semi-discrete hyperbolic equations admitting five dimensional characteristic x-ring
Zheltukhın, Kostyantyn (2016-01-01)
The necessary and sufficient conditions for a hyperbolic semi-discrete equation to have five dimensional characteristic x-ring are derived. For any given chain, the derived conditions are easily verifiable by straightforward calculations.
Citation Formats
D. Dinler and M. K. Tural, “Semi supervised Clustering with Regional Data Objects,” 2015, Accessed: 00, 2021. [Online]. Available: