Phishing is a very dangerous security threat that affects individuals as well companies and organizations. To fight the risks associated with this threat, it important to detect phishing websites in timely manner. Machine learning models work for purpose they can predict cases, using information on underlying websites. In paper, we contribute research detection of by proposing an explainable ma...

Data streams are ubiquitous and related to the proliferation of low-cost mobile devices, sensors, wireless networks Internet Things. While it is well known that complex phenomena not stationary exhibit a concept drift when observed for sufficiently long time, relatively few studies have addressed problem feature drift. In this paper, variation QuickReduct algorithm suitable process data propose...

Facial feature detection is considered an important computer vision task that is used for many real world applications. Current advancements in computer vision have come up with many proposed facial feature detection approaches, such as Deformable Parts Model (DPM), that provide good accuracy in the detection of key facial features, but mainly in frontal poses. When presented with side profile ...

In the visualization of flow simulation data, feature detectors often tend to result in overly rich response, making some sort of filtering or simplification necessary to convey meaningful images. In this paper we present an approach that builds upon a decomposition of the flow field according to dynamical importance of different scales of motion energy. Focusing on the high-energy scales leads...

In this paper, we present the methodology we applied in our submission to the NIST TRECVID’2007 evaluation. We participated in the High-level Feature Extraction task. Our approach is based on the use of a Forest of Fuzzy Decision Trees combined with the RankBoost algorithm. 1 Structured Abstract Summary Here we present the contribution of the University of Paris 6 at TRECVID 2007 [6]. It concer...