Army Model P-39Q-1 Airplane

Pilot's manual/flight working directions for the P-39Q-1 Airacobra

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Pentland, and D. Petkovic, Workshop Report: NSF-ARPA Workshop on Visual information Management Systems, Cambridge, Mass, USA, June 1995. A. Kankanhalli, H. J. Zhang, and C. Y. Low, "Using texture for image retrieval," Third Int. Conf on Automation, Robotics and Computer Vision, pp. 935-939, Singapore, Nov. 1994. H. Kauppinen, T. Seppnaen, and M. Pietikainen, "An experimental comparison of autoregressive and Fourier-based descriptors in 20 shape classification," IEEE Trans. Pattern Anal. , Vol. 2, pp.

Manjunath, "Edge flow: a framework of boundary detection and image segmentation," iEEE into Con! on Computer Vision and Pattern Recognition, pp. 744-749, Puerto Rico, June 1997. S. G. Mallat, "A theory for multiresolution signal decomposition: the wavelet representation," IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. II, pp. 674-693, July 1989. B. S. Manjunath, and W. Y. Ma, "Texture features for browsing and retrieval of image data," iEEE Trans. on Pattern Analysis and Machine intelligence, Vol.

On the other 22 Chapter 1 hand, query results can be refined to include more relevant candidates through the relevance feedback of users. Updating the retrieval results based on the user's feedback can be achieved by updating the images, the feature models, the weights of features in similarity distance, and select different similarity measures. Details will be introduced in Chapter 3. Although content-based retrieval provides an intelligent and automatic solution for efficient searching of images, the majority of current techniques are based on low level features.

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