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We analysed the most recent version of the CAR dataset, using geographic information system analytical tools.
Figure 8 a, b illustrates the detections done by our source car detector on the UIUC car dataset [44] and the Caltech cars 2001 (Rear) dataset [45], respectively.
With the Car dataset, decision tree achieves 95% classification accuracy which is equivalent to the results obtained for other feature selection methods.
The negative samples were cropped randomly from video frames and from the INRIA Person dataset [9] and the INRIA car dataset [43].
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Proposed aggressiveness detection method also tested with real-world data from 100-car dataset [42].
The vehicle speed, lane deviation and collision time data are directly present at 100-car dataset.
FGVC-car dataset [27] (cars): it is composed of 16,185 images of cars from 196 classes.
Fig. 8 Results of source car detector on a UIUC cars dataset and b Caltech cars 2001 (rear) dataset.
Some examples are aircraft datasets [6, 7]; Caltech-UCSD bird species dataset [8] consisting of 12 K images, car make, and model datasets; Standford cars dataset [9] containing 16 K car images; and CompCars dataset [10] of 130 K images.
The benchmark car evaluation dataset from UCI machine learning repository is used for training and testing the SMK.
crocodilus; CAR, Car.
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Justyna Jupowicz-Kozak
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