Ev ve Ofis taşıma sektöründe lider olmak.Teknolojiyi takip ederek bunu müşteri menuniyeti amacı için kullanmak.Sektörde marka olmak.
İstanbul evden eve nakliyat
Misyonumuz sayesinde edindiğimiz müşteri memnuniyeti ve güven ile müşterilerimizin bizi tavsiye etmelerini sağlamak.
Performance Prediction
for Model-based Object Recognition
Presented by: Xiaobing Qian
ABSTRACT: In this presentation, I will introduce the approach
to predict the probability of correct recognition for model-based,
point-based object recognition. The method considers data
distortion factors such as perturbation, occlusion, and clutter.
Performance is predicted in two stages. In the first stage,
the PDF of the vote between each pair of views in the database
is computed out. In the second stage, the PDF is used to predict
the lower/upper bound of PCR or itself. The validity of our
predictions is demonstrated by the experiment on synthetic
SAR data.
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