UAV-Based Situational Awareness System Using Deep Learning
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Advances in camera sensor technology and its manufacturing process now allow high quality image acquisition with low-cost devices. Moreover, the latest significant increase in computational capacity of the processing units enables incorporation of more com ...
Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capturing ...
We propose a deep-learning approach for people detection on depth imagery. The approach is designed to be deployed as an autonomous appliance for identifying people attacks and intrusion in video surveillance scenarios. To this end, we propose a fully-conv ...
Image super-resolution reconstructs a higher-resolution image from the observed low-resolution image. In recent years, machine learning models have been widely employed and deep learning networks have achieved state-of-the-art super-resolution performance. ...
Although disaster risk management is becoming increasingly important in development cooperation, there is still a lack of robust evidence regarding its effectiveness. Few studies based on a counterfactual have been conducted in the fields of disaster manag ...
Recognizing eye movements is important for gaze behavior understanding like in human communication analysis (human-human or robot interactions) or for diagnosis (medical, reading impairments). In this paper, we address this task using remote RGB-D sensors ...
Lightweight, autonomous drones are soon expected to be used in a wide variety of tasks such as aerial surveillance, delivery, or monitoring of existing architectures. A large body of literature in robotic perception and control exists. Existing methods are ...
Unmanned Aerial Vehicles are becoming increasingly popular for a broad variety of tasks ranging from aerial imagery to objects delivery. With the expansion of the areas, where drones can be efficiently used, the collision risk with other flying objects inc ...
We report on the use of deep learning algorithms to perform depth recovery in multiview imaging. We show that if enough training data are provided, a neural network such as multilayer perceptron can be trained to recover the depth in multiview imaging as a ...
Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife monitoring, with several advantages over traditional field-based methods. They have readily been used to count birds, marine mammals and large herbivores in different environments, tasks ...