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A novel framework for anomaly detection in crowded scenes is presented. Three properties are identified as important for the design of a localized video representation suitable for anomaly detection in such scenes: 1) joint modeling of appearance and dynamics of the scene, and the abilities to detect 2) temporal, and 3) spatial abnormalities. The model for(More)
The detection and localization of anomalous behaviors in crowded scenes is considered, and a joint detector of temporal and spatial anomalies is proposed. The proposed detector is based on a video representation that accounts for both appearance and dynamics, using a set of mixture of dynamic textures models. These models are used to implement 1) a(More)
The problem of adaptively selecting pooling regions for the classification of complex video events is considered. Complex events are defined as events composed of several characteristic behaviors, whose temporal configuration can change from sequence to sequence. A dynamic pooling operator is defined so as to enable a unified solution to the problems of(More)
In this work, we propose a novel video representation for activity recognition that models video dynamics with attributes of activities. A video sequence is decomposed into short-term segments, which are characterized by the dynamics of their attributes. These segments are modeled by a dictionary of attribute dynamics templates, which are implemented by a(More)
Previous approaches to action recognition with deep features tend to process video frames only within a small temporal region, and do not model long-range dynamic information explicitly. However, such information is important for the accurate recognition of actions, especially for the discrimination of complex activities that share sub-actions, and when(More)
A generalized formulation of the multiple instance learning problem is considered. Under this formulation, both positive and negative bags are soft, in the sense that negative bags can also contain positive instances. This reflects a problem setting commonly found in practical applications, where labeling noise appears on both positive and negative training(More)
OBJECTIVES We have recently developed a new personal sampling system for the real-time measurement of the protection provided by respirators against airborne dust and micro-organisms. The objective of this study was to evaluate the performance characteristics of the new sampling system in both laboratory and field conditions. METHODS The measurements were(More)
Ginkgo biloba L., an extant primitive gymnosperm species, occupies an important position in the evolution of the plant kingdom. Furthermore, its leaves contain a large number of active, medicinally valuable compounds; therefore, it is also an important tree economically. MicroRNAs (miRNAs) are important regulators of gene expression implicated in(More)
High-throughput sequencing and subsequent analysis identified multiple miRNAs closely related to ovule, indicating that miRNAs are important in Ginkgo biloba ovule. MicroRNAs (miRNAs) are small, noncoding, regulatory RNAs that play crucial regulatory roles in the process of plant growth and development. However, limited information regarding their functions(More)