Measurements of microwave power can be made directly, usually with a thermistor based detector and meter.
These points are detected in the facial region by scale invariant feature based detectors, and then tracked through the video sequences using multiple Differential Evolution-Markov Chain (DE-MC) particle filters with kernel correlation techniques.
The final C36 was derived from the ROIs by using a combination of part based detectors and a consensus of shape exemplars.
Three popular MUDs are considered; two parallel interference cancellation (PIC) based detectors and one full maximum a-posteriori probability (MAP) detector.
By using a correlation based detector, the similarity between the extracted watermark, and the series of the possible watermarks,, can be calculated to determine the embedded watermark.
In this paper we investigate and verify the performance of the new 10B based detector concept and its adoption for the POWTEX diffractometer, which is designed for the detection of thermal neutrons with predicted detection efficiencies of 75 50% for neutron energies of 10 100 meV, respectively.
Compared to the covariance matrix based detector, the proposed model-based adaptive detectors have significantly decreased the training requirements and the computation complexity.
Compared to the covariance matrix based detector, all of the proposed adaptive detectors can handle the training-limited case and significantly decreased the computation complexity in compound-Gaussian environment.
A basic implementation of this model is developed based on the SS watermarking with LC-based detector and the quantization watermarking using binary DM.
Cyclostationary based detector is efficient and more robust than energy detector [9], which is highly susceptible to noise uncertainty.
We used a sensitive CMOS based detector (Tietz Video and Image Processing Systems GmbH), previously shown to be beneficial for electron diffraction studies (Tani et al., 2009) and modified our data collection procedure.
