Daniela Cuza

Daniela Cuza
University of Padova | UNIPD · Department of Information Engineering

About

8
Publications
526
Reads
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18
Citations
Citations since 2017
8 Research Items
18 Citations
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20172018201920202021202220230246810
20172018201920202021202220230246810

Publications

Publications (8)
Article
Full-text available
Ecoacoustics is arguably the best method for monitoring marine environments, but analyzing and interpreting acoustic data has traditionally demanded substantial human supervision and resources. These bottlenecks can be addressed by harnessing contemporary methods for automated audio signal analysis. This paper focuses on the problem of assessing do...
Preprint
Full-text available
To effectively preserve marine environments and manage endangered species, it is necessary to employ efficient, precise, and scalable solutions for environmental monitoring. Ecoacoustics provides several benefits as it enables non-intrusive, prolonged sampling of environmental sounds, making it a promising tool for conducting biodiversity surveys....
Chapter
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Globally, colorectal cancer is one of the leading causes of mortality. Colonoscopies and the early removal of polys significantly increase the survival rate of this cancer, but this intervention depends on the accurate detection of polys in the surrounding tissues. Missing a poly has serious consequences. One way to guard against human error is to...
Article
Full-text available
Recognizing objects in images requires complex skills that involve knowledge about the context and the ability to identify the borders of the objects. In computer vision, this task is called semantic segmentation and it pertains to the classification of each pixel in an image. The task is of main importance in many real-life scenarios: in autonomou...
Preprint
Full-text available
Semantic segmentation consists in classifying each pixel of an image by assigning it to a specific label chosen from a set of all the available ones. During the last few years, a lot of attention shifted to this kind of task. Many computer vision researchers tried to apply autoencoder structures to develop models that can learn the semantics of the...

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