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—Robust face detection in the wild is one of the ultimate components to support various facial related problems, i.e. unconstrained face recognition, facial periocular recognition, facial landmarking and pose estimation, facial expression recognition, 3D facial model construction, etc. Although the face detection problem has been intensely studied for(More)
Robust face detection is one of the most important preprocessing steps to support facial expression analysis, facial landmarking, face recognition, pose estimation, building of 3D facial models, etc. Although this topic has been intensely studied for decades, it is still challenging due to numerous variants of face images in real-world scenarios. In this(More)
Weakly supervised methods have recently become one of the most popular machine learning methods since they are able to be used on large-scale datasets without the critical requirement of richly annotated data. In this paper, we present a novel, self-taught, discriminative facial feature analysis approach in the weakly supervised framework. Our method can(More)
Plasmodium of Physarum polycephalum is a model species of eukaryotic microorganisms for studying amoeboid movement. Plasmodium's natural movements are characterized by the rhythmic back-and-forth streaming of cytoplasm peristalsis, which results in the directed locomotion of plasmodium, and the periodic change of the electric potential on the surface of(More)
In this paper, we present an advanced deep learning based approach to automatically determine whether a driver is using a cell-phone as well as detect if his/her hands are on the steering wheel (i.e. counting the number of hands on the wheel). To robustly detect small objects such as hands, we propose Multiple Scale Faster-RCNN (MSFRCNN) approach that uses(More)
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