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Information, Volume 13, Issue 1

January 2022 - 42 articles

Cover Story: Two-dimensional space embeddings are a popular means to gain insight into high-dimensional data. However, these embeddings suffer from distortions that occur both at the global inter-cluster and the local intra-cluster levels. The former leads to misinterpretation of the distances between the various N–D cluster populations, while the latter hampers the appreciation of their individual shapes and composition, which we call cluster appearance. In this paper, we propose techniques to overcome these limitations by conveying the N–D cluster appearance through N–D-based Scagnostics metrics and a framework inspired by illustrative design. We validated and refined our design choices via a series of user studies. View this paper

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Article

29 Citations

5,779 Views

12 Pages

Unpaired Underwater Image Enhancement Based on CycleGAN

Rong Du,
Weiwei Li,
Shudong Chen,
Congying Li and
Yong Zhang

Information2022, 13(1), 1;https://doi.org/10.3390/info13010001

22 December 2021

Underwater image enhancement recovers degraded underwater images to produce corresponding clear images. Image enhancement methods based on deep learning usually use paired data to train the model, while such paired data, e.g., the degraded images and...

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Article

26 Citations

6,904 Views

21 Pages

Low-Altitude Aerial Video Surveillance via One-Class SVM Anomaly Detection from Textural Features in UAV Images

Danilo Avola,
Luigi Cinque,
Angelo Di Mambro,
Anxhelo Diko,
Alessio Fagioli,
Gian Luca Foresti,
Marco Raoul Marini,
Alessio Mecca and
Daniele Pannone

Information2022, 13(1), 2;https://doi.org/10.3390/info13010002

22 December 2021

In recent years, small-scale Unmanned Aerial Vehicles (UAVs) have been used in many video surveillance applications, such as vehicle tracking, border control, dangerous object detection, and many others. Anomaly detection can represent a prerequisite...

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Information - ISSN 2078-2489

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