This paper introduces an online model for object detection in videos designed to run in real-time on lowpowered mobile and embedded devices. Our approach combines fast single-image object detection with convolutional long short term memory (LSTM) layers to create an interweaved recurrent-convolutional architecture. Additionally, we propose an efficient Bottleneck-LSTM layer that significantly r...

Single-sample methods of bottleneck detection are now routine analyses in studies of wild populations and conservation genetics. Three common approaches to bottleneck detection are the heterozygosity excess, mode-shift, and M-ratio tests. Empirical groundtruthing of these methods is difficult, but their performances are critical for the accurate reconstruction of population demography. We use t...

Single-sample methods of bottleneck detection are now routine analyses in studies of wild populations and conservation genetics. Three common approaches to bottleneck detection are the heterozygosity excess, mode-shift, and Mratio tests. Empirical groundtruthing of these methods is difficult, but their performances are critical for the accurate reconstruction of population demography. We use tw...

Persistently saturated links are abnormal conditions that indicate bottlenecks in Internet traffic. Network operators are interested in detecting such links for troubleshooting, to improve capacity planning and traffic estimation, and to detect denial-of-service attacks. Currently bottleneck links can be detected either locally, through SNMP information, or remotely, through active probing or p...