Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Abdelhamid Daamouche"'
Publikováno v:
Bulletin of the Polish Academy of Sciences: Technical Sciences, Vol 70, Iss 6 (2022)
Face Sketch Recognition (FSR) presents a severe challenge to conventional recognition paradigms developed basically to match face photos. This challenge is mainly due to the large texture discrepancy between face sketches, characterized by shape exag
Externí odkaz:
https://doaj.org/article/c2499c0e1ff04ea29fdac504e89bf332
Publikováno v:
International Journal of Remote Sensing. 43:1703-1723
Publikováno v:
2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE).
Publikováno v:
2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS).
Publikováno v:
The International Arab Journal of Information Technology. 17:480-487
The QRS detection is a crucial step in ECG signal analysis; it has a great impact on the beats segmentation and in the final classification of the ECG signal. The Pan-Tompkins is one of the first and best-performing algorithms for QRS detection. It p
Publikováno v:
IEEE Geoscience and Remote Sensing Magazine. 7:174-177
Autor:
Abdelhamid Daamouche, Yasmine Makhlouf
Publikováno v:
Expert Systems with Applications. 119:342-349
Road extraction from very high resolution remotely sensed images is crucial in many urban applications. Acquiring automatically up-to-date and accurate information about roads is significant for various intelligent applications such as smart vehicle
Publikováno v:
Journal of Computer Science. 15:108-117
Publikováno v:
Multimedia Tools and Applications.
Accurate QRS detection is crucial for reliable ECG signal analysis and the development of automatic diagnosis tools. In this paper, we propose a simple yet efficient new algorithm for QRS detection using the Stationary Wavelet Transform (SWT). The wa
Autor:
Abdelhamid Daamouche, Chahrazed Fiala
Publikováno v:
2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS).
this paper presents a new approach to extract features from high resolution images inspired by the sift descriptor and gabor features. both of these two methods are powerful when used separately or together in region-based or pixel-based classificati