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Committee machines for facial-gender recognition
International Journal of Hybrid Intelligent Systems, 2009This paper presents a new approach for building a committee machine (LVQCM) that is based on learning vector quantization (LVQ) neural networks. The proposed committee machine was then applied to solve the problem of facial gender recognition. Design of individual classifiers is time consuming and results in inaccurate and unstable classifiers ...
Hazem M. Raafat +2 more
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Gender Recognition in Non Controlled Environments
18th International Conference on Pattern Recognition (ICPR'06), 2006In most of the automatic face classification applications, images should be captured in natural environments, where partial occlusions or high local changes in the illumination are frequent. For this reason, face classification tasks in uncontrolled environment are still nowadays unsolved problems, given that the loss of information caused by these ...
Àgata Lapedriza +2 more
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Using gait information for gender recognition
2010 10th International Conference on Intelligent Systems Design and Applications, 2010Gender recognition is a hot research topic in recent years. Human-machine interfaces or video surveillance can be greatly improved if human gender can be recognized automatically. In this study, an embedded hidden Markov model is used for gender recognition.
Chuan-Yu Chang, Tai-Hua Wu
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Facial Recognition, Expression Recognition, and Gender Identification
2018Face recognition has many important applications in areas such as public surveillance and security, identity verification in the digital world, and modeling techniques in multimedia data management. Facial expression recognition is also important for targeted marketing, medical analysis, and human–robot interaction.
Shraddha Mane, Gauri Shah
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A system for gender recognition on mobile robots
Proceedings of the 2nd International Conference on Applications of Intelligent Systems, 2019The combination of artificial intelligence and robotics opens the way to disruptive future developments in the industrial and collaborative robotics. The recent advances of the deep learning technologies materialize the possibility to provide a robot perceptive and reasoning skills and, consequently, the capability to autonomously interact with a human.
Foggia, Pasquale +4 more
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Head-shoulder based gender recognition
2013 IEEE International Conference on Image Processing, 2013This paper proposes a novel gender recognition method based on the head-shoulder part of human body. The head-shoulder area contains much information that could be cues to infer the gender of a person, such as hair-style, face, neckline style and so on.
Min Li 0022 +4 more
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Gender Recognition Using Cognitive Modeling
2012In this work, we use cognitive modeling to estimate the "gender strength" of frontal faces, a continuous class variable, superseding the traditional binary class labeling. To incorporate this continuous variable we suggest a novel linear gender classification algorithm, the Gender Strength Regression.
Jens Fagertun +2 more
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Abstract European human rights following the Second World War came about because of an urgent need for laws to protect minority groups from the type of systemic, institutional, or personal prejudices that led to the holocaust.
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Face recognition using gender information
2009 16th IEEE International Conference on Image Processing (ICIP), 2009In this paper, we propose a novel method using gender information for achieving better performances of face recognition systems. Gender is one of the important factors for recognizing appearance of human faces and there are many studies on gender classifications such as [1].
Wonjun Hwang +4 more
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Evaluation of Keypoint Descriptors for Gender Recognition
2014Gender recognition is a relevant problem due to the number and importance of its possible application areas. The challenge is to achieve high recognition rates in the shortest possible time. Most studies are based on Local Binary Patterns (LBP) and its variants to estimate gender.
Florencia Soledad Iglesias +3 more
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