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A Fast Statistical Approach for Human Activity Recognition

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International Journal of Intelligence Science 2012年第1期2卷 9-15页

作者： samy sadek Ayoub Al-Hamadi Bernd Michaelis Usama Sayed 不详

An essential part of any activity recognition system claiming be truly real-time is the ability to perform feature extraction in real-time. We present, in this paper, a quite simple and computationally tractable approach for real-time human activity recognition that is based on simple statistical features. These features are simple and relatively small, accordingly they are easy and fast to be calculated, and further form a relatively low-dimensional feature space in which classification can be carried out robustly. On the Weizmann publicly benchmark dataset, promising results (i.e. 97.8%) have been achieved, showing the effectiveness of the proposed approach compared to the-state-of-the-art. Furthermore, the approach is quite fast and thus can provide timing guarantees to real-time applications.

关键词： Activity Recognition Motion Analysis Statistical Moments Video Interpretation

Face Detection and Localization in Color Images: An Efficient Neural Approach

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Journal of Software Engineering and Applications 2011年第12期4卷 682-687页

作者： samy sadek Ayoub Al-Hamadi Bernd Michaelis Usama Sayed 不详

Automatic face detection and localization is a key problem in many computer vision tasks. In this paper, a simple yet effective approach for detecting and locating human faces in color images is proposed. The contribution of this paper is twofold. First, a particular reference to face detection techniques along with a background to neural networks is given. Second, and maybe most importantly, an adaptive cubic-spline neural network is designed to be used to detect and locate human faces in uncontrolled environments. The experimental results conducted on our test set show the effectiveness of the proposed approach and it can compare favorably with other state-of-the-art approaches in the literature.

关键词： Human Face Detection and Localization Spline Activation Function Color Moments Human-Computer Interaction

A Statistical Framework for Real-Time Traffic Accident Recognition

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Journal of Signal and Information Processing 2010年第1期1卷 77-81页

作者： samy sadek Ayoub Al-Hamadi Bernd Michaelis Usama Sayed 不详

Over the past decade, automatic traffic accident recognition has become a prominent objective in the area of machine vision and pattern recognition because of its immense application potential in developing autonomous Intelligent Transportation Systems (ITS). In this paper, we present a new framework toward a real-time automated recognition of traffic accident based on the Histogram of Flow Gradient (HFG) and statistical logistic regression analysis. First, optical flow is estimated and the HFG is constructed from video shots. Then vehicle patterns are clustered based on the HFG-features. By using logistic regression analysis to fit data to logistic curves, the classifier model is generated. Finally, the trajectory of the vehicle by which the accident was occasioned, is determined and recorded. The experimental results on real video sequences demonstrate the efficiency and the applicability of the framework and show it is of higher robustness and can comfortably provide latency guarantees to real-time surveillance and traffic monitoring applications.

关键词： Activity Pattern Automatic Traffic Accident Recognition Flow Gradient Logistic Model

Potential Insecticidal Effect of a Wasp (Polistes dominulus) and a Bee (Apis mellifera) Venoms in Controlling Spodoptera littoralis

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Advances in Entomology 2022年第4期10卷 300-319页

作者： Reham Z. sadek Shereen M. El Banna Fayez M. Semida samy M. Zalat Zoology Department Faculty of Science Suez Canal University Ismailia Egypt

Cotton leaf worm, Spodoptera littoralis, is considered one of the most common arthropod pests that contribute to crop devastation of cotton. Previously, agricultural pests were controlled through the application of chemical insecticides. However, insecticide-resistant insect populations emergence, as well as increasing concerns about the environmental and human health risks. Venomous animals introduce valuable sources of bioactive compounds which are employed for defence. Some of these toxins have high phyletic specificity, making them appropriate for use in IPM programs. This study aims to test the insecticidal effects of Polistes dominulus and Apis mellifera venoms. Crude venoms were examined for their insecticidal effect against cotton leaf worms by four different application methods including: leaf dipping, integument dropping, spraying, and injection. The data demonstrated a strong response to purified (Polistes dominulus) venom at an initial time than that of honey bee (Apis mellifera) which increases response with increasing the dose and the time interval. A dosage of 0.015 - 0.16 ml of both venoms had notably varied in LD50 values on Spodoptera littoralis that showed higher wasp venom toxicity. Cotton leaf worms showed more susceptibility and mortality to the Polistes sp. venom than that of honey bees.

关键词： Social Insects Honey Bee Yellow Jacket Enzymes Pest Control Bio-Insecticides Biological Control