Yong Shean Chong

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We present an efficient method for detecting anomalies in videos. Recent applications of convolutional neural networks have shown promises of convolutional layers for object detection and recognition, especially in images. However, convolutional neural networks are supervised and require labels as learning signals. We propose a spatiotemporal architecture(More)
An atropisomeric molecular balance was developed to study face-to-face arene-arene interactions. The balance has a large central 1,4,5,8-naphthalene diimide surface that forms intramolecular arene-arene interactions with two pendent arms. The balance adopts distinct syn and anti isomers with varying numbers of intramolecular interactions. Thus, the strength(More)
While vehicle license plate recognition (VLPR) is usually done with a sliding window approach, it can have limited performance on datasets with characters that are of variable width. This can be solved by hand-crafting algorithms to prescale the characters. While this approach can work fairly well, the recognizer is only aware of the pixels within each(More)
This review article surveys the current progresses made toward video-based anomaly detection. We address the most fundamental aspect for video anomaly detection, that is, video feature representation. Much research works have been done in finding the right representation to perform anomaly detection in video streams accurately with an acceptable false alarm(More)
Parallel computing is currently used in many engineering problems. However, because of limitations in curriculum design, it is not always possible to offer students specific formal teaching in this topic. Furthermore, parallel machines are still too expensive for many institutions. The latest microprocessors, such as Intel’s Pentium III and IV, embody(More)
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