Detecting anomalies in surveillance videos is an important research problem in computer vision. In this thesis, we propose two deep network architectures for anomaly detection, Anomaly Detection Network (ADNet) and Anomaly ...

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the ...

In this study, our aim is to make an evaluation of the interplay between environment-based cues, namely speed, scene complexity and stereoscopic rendering parameters, and the discomfort felt in the form of cybersickness ...

The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number ...

Nowadays, sellers need very good strategy to keep their customers’ loyalty and to attract new customers to their shops. One of the important ways to accomplish this task is to present new and interesting items to their ...

This article presents a probabilistic hierarchical clustering model for morphological segmentation. In contrast to existing approaches to morphology learning, our method allows learning hierarchical organization of word ...

The problem of video captioning can be defined as describing a video content by using natural language in a way that a person can identify the video by performing information extraction from the given videos. Video captioning ...

Because of the inflection of many word forms from the same root in agglutinative languages such as Turkish, modeling the words as a whole causes sparsity problem. Therefore, rather than handling the word as a whole, ...

Emotion analysis means to automatic determination of the emotions in any digital content. It has become a necessity to distill and evaluate with emotion analysis the big data that emerged as a result of the dizzying ...

In this work, we look into the problem of recognizing two-person interactions in videos. Our method integrates multiple visual features in a weakly supervised manner by utilizing an embedding-based multiple instance learning ...