Sentence examples for classification images from inspiring English sources

Most of the theory supporting our understanding of classification images relies on standard signal detection models and the use of normally distributed stimulus noise.

They assessed quantitatively the benefits of the self-tuning filer as preprocessor for image classification: images were classified as containing or not man-made objects [14, 15].

In color histogram-based classification, images with similar colors are represented in the same color histogram because similar colors fall into the same bins due to the quantization.

The legend is shown in Fig. 12 Fig. 14 Comparison of terrain classification images of the Kanto District and its surroundings.

c Iwahashi and Pike (2007), using a 1 km DEM Fig. 15 Comparison of the terrain classification images of the Rub' al khali.

These findings make it possible to use and interpret classification images in tasks where observers' decision strategies may not conform to classic signal detection models such as the difference rule, and in tasks where the stimulus noise is non-Gaussian.

Currently the service supports text classification, image classification, object detection and semantic segmentation.

Eerily, a facelike classification image emerged from the collective brain activity of people experiencing pareidolia.

Fig. 16 Shaded terrain classification image in the Krasnoyarsk region (Russia) Fig. 17 Shaded terrain classification image from central New Zealand Fig. 18 Shaded terrain classification image of the Cameroon line and Niger delta.

The analysis has been realized using multitemporal Landsat TM images through Supervised classification, image processing, vectorialization and GIS tools.

Fig. 19 Shaded terrain classification image of the Central Plain of Thailand and its surroundings.