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| Arthur Filippidis, L.c. Jain, N. Martin, "Fusion of Intelligent Agents for the Detection of Aircraft in SAR Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 4, pp. 378-384, April, 2000. | |||
| BibTex | x | ||
| @article{ 10.1109/34.845380, author = {Arthur Filippidis and L.c. Jain and N. Martin}, title = {Fusion of Intelligent Agents for the Detection of Aircraft in SAR Images}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {22}, number = {4}, issn = {0162-8828}, year = {2000}, pages = {378-384}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.845380}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Fusion of Intelligent Agents for the Detection of Aircraft in SAR Images IS - 4 SN - 0162-8828 SP378 EP384 EPD - 378-384 A1 - Arthur Filippidis, A1 - L.c. Jain, A1 - N. Martin, PY - 2000 KW - Fusion KW - Automatic Target Recognition. VL - 22 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—Receiver Operating Curves are used in the analysis of 20 images using a novel Automatic Target Recognition (ATR) Fusion System. Fuzzy reasoning is used to improve the accuracy of the automatic detection of aircraft in Synthetic Aperture Radar (SAR) images using a priori knowledge derived from color aerial photographs. The images taken by the two different sensors are taken at different times. In summarizing the results of our experiments using real and generated targets with noise for a probability of detection of 91.5 percent using the ATR fusion technique, we have improved our false alarm rates by approximately 17 percent over using texture classification.
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