A Simple Deep Learning Architecture for City-scale Vehicle Re-identification

The task of vehicle re-identification aims to identify a vehicle across different cameras with non overlapping fields of view and it is a challenging research problem due to viewpoint orientation, scene occlusions and intrinsic inter-class similarity of the data. In this paper, we propose a simplistic approach for one-shot vehicle re-identification based on a siamese/triple convolutional architecture for feature representation. Our method involves learning a feature space in which the vehicles of the same identities are projected closer to one another compared to those with different identities. Moreover, we provide an extensive evaluation of loss functions, including a novel combination of triplet loss with classification loss, and other network parameters applied to our vehicle re-identification system. Compared to most existing state-of-the-art approaches, our approach is simpler and more straightforward for training, utilizing only identity-level annotations. The proposed method is evaluated on the large-scale CityFlow-ReID dataset

Report: Hate Speech, Behaviour and Crimes in Cyprus

Η παρούσα έκδοση αποτελεί μέρος ενός ευρύτερου 18-μηνου σχεδίου με θέμα την Αντιμετώπιση της Ρητορικής, Συμπεριφορών και Εγκλημάτων Μίσους στην Κύπρο (Confronting Hate Speech, Behaviour and Crimes in Cyprus) το οποίο ανέλαβε το Ινστιτούτο Ερευνών ΠΡΟΜΗΘΕΑΣ τον Απρίλιο του 2014 και συγχρηματοδοτείται από την Ισλανδία, το Λίχτενσταϊν και τη Νορβηγία μέσω του χρηματοδοτικού μηχανισμού EEA GRANTS και από την Κυπριακή Δημοκρατία. Στοχεύει σε μια, κατά το δυνατόν, ολοκληρωμένη έρευνα και καταγραφή της έκτασης του προβλήματος της ρητορικής, συμπεριφορών και εγκλημάτων μίσους στο κοινωνικό περιβάλλον της Κύπρου (στην ελληνική και την τουρκοκυπριακή κοινότητα). Η μελέτη οριοθετεί το ιστορικό, το σύγχρονο, καθώς και το νομικό πλαίσιο του ζητήματος, αξιοποιώντας δευτερογενή, αλλά και πρωτογενή στοιχεία. This publication is part of a larger 18-month project on Confronting Hate Speech, Behaviour and Crimes in Cyprus, which was assumed by the Promitheas Research Institute in April 2014 and was funded by Iceland, Liechtenstein and Norway through the financial mechanism of EEA GRANTS and by the Republic of Cyprus. It aims to present a well-rounded research investigation and to record the extent of the problem of hate speech, behaviors and crime in the social environment of Cyprus (in the Greek and Turkish Cypriot communities). The study defines the historical, contemporary and legal framework of the issue, by utilizing secondary and primary data

A simple deep learning architecture for city-scale vehicle re-identification

The task of vehicle re-identification aims to identify a vehicle across different cameras with non overlapping fields of view and it is a challenging research problem due to viewpoint orientation, scene occlusions and intrinsic inter-class similarity of the data. In this paper, we propose a simplistic approach for one-shot vehicle re-identification based on a siamese/triple convolutional architecture for feature representation. Our method involves learning a feature space in which the vehicles of the same identities are projected closer to one another compared to those with different identities. Moreover, we provide an extensive evaluation of loss functions, including a novel combination of triplet loss with classification loss, and other network parameters applied to our vehicle re-identification system. Compared to most existing state-of-the-art approaches, our approach is simpler and more straightforward for training, utilizing only identity-level annotations. The proposed method is evaluated on the large-scale CityFlow-ReID dataset