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Now showing items 11-18 of 18
Kamera ve ataletsel ölçüm birimi iç kalibrasyonu
(IEEE, 2013)
In this paper, we address the problem of internal calibration of a camera and an inertial measurement unit (IMU). The internal calibration of a camera and an IMU requires the determination of the relative orientation and ...
Effect of camera-IMU displacement calibration error on tracking performance
(IEEE, 2015)
Due to their complementary properties, inertial measurement units (IMU) and cameras are used in ego-motion tracking applications. For this, the relative rotation and displacement between the camera and IMU reference frames ...
Hareketten yapı çıkarımı için görsel kullanıcı arayüzü
(IEEE, 2014)
The usage of computer vision applications such as 3D reconstruction, motion tracking and augmented reality gradually increases. The first and the most important stage of these kind of applications is estimating the 3D scene ...
Bispectrum estimation using a MISO autoregressive model
(Springer International Publishing, 2016)
Bispectra are third-order statistics that have been used extensively in analyzing nonlinear and non-Gaussian data. Bispectrum of a process can be computed as the Fourier transform of its bicumulant sequence. It is in general ...
Automatic fall detection for elderly by using features extracted from skeletal data
(IEEE, 2013)
Automatic detection of unusual events such as falls is very important especially for elderly people living alone. Realtime detection of these events can reduce the health risks associated with a fall. In this paper, we ...
RANSAC-based training data selection on spectral features for emotion recognition from spontaneous speech
(Springer International Publishing, 2011)
Training datasets containing spontaneous emotional speech are often imperfect due the ambiguities and difficulties of labeling such data by human observers. In this paper, we present a Random Sampling Consensus (RANSAC) ...
Curriculum learning for face recognition
(IEEE, 2021)
We present a novel curriculum learning (CL) algorithm for face recognition using convolutional neural networks. Curriculum learning is inspired by the fact that humans learn better, when the presented information is organized ...
More learning with less labeling for face recognition
(Elsevier, 2023-05)
In this paper, we propose an improved face recognition framework where the training is started with a small set of human annotated face images and then new images are incorporated into the training set with minimum human ...
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