Additional file 1: Figure S1. Classification performance of the algorithm used in the study, showing (A) the global confusion matrix (on labelled data) and (B) the receiver operating characteristic curves for the diving, floating on water and flying classes, respectively. dv = diving, ent_wat = entering water, wat = floating on water, takeoff = taking off, fly = flying
Acoustic positional telemetry systems (APTs) represent a novel approach to study the behaviour of fr...
Dive data collected from archival and satellite tags can provide valuable information on foraging ac...
Automatic algorithms for the detection and classification of sound are essential to the analysis of ...
Additional file 2: Figure S2. Performances of the algorithm (after classification and revision) on t...
Additional file 3: Figure S3. (A) Performance of automatic classifications as measured by the global...
Additional file 4: Figure S4. Performance of automatic classifications as measured by the global acc...
Additional file 6: Table S2. Systematic review on published articles that automatically classified a...
Abstract Background Studies on animal behaviour often involve the quantification of the occurrence a...
Supervised dive classification is a commonly used technique for categorising time-depth profiles of ...
Knowledge of the diving behaviour of aquatic animals expanded considerablywith the invention of time...
The behavior of many wild animals remains a mystery, as it is difficult to quantify behaviour of spe...
This file explains the variables in the acoustic telemetry detection dataset that accompanies: Kraus...
For diving animals, animal-borne sensors are used to collect time–depth information for studying beh...
To fulfill information gaps of underwater animal behavior, variety of animal-borne observation syste...
Abstract: Acceleration data loggers were attached to five adult Adelie penguins at Hukuro Cove, Lutz...
Acoustic positional telemetry systems (APTs) represent a novel approach to study the behaviour of fr...
Dive data collected from archival and satellite tags can provide valuable information on foraging ac...
Automatic algorithms for the detection and classification of sound are essential to the analysis of ...
Additional file 2: Figure S2. Performances of the algorithm (after classification and revision) on t...
Additional file 3: Figure S3. (A) Performance of automatic classifications as measured by the global...
Additional file 4: Figure S4. Performance of automatic classifications as measured by the global acc...
Additional file 6: Table S2. Systematic review on published articles that automatically classified a...
Abstract Background Studies on animal behaviour often involve the quantification of the occurrence a...
Supervised dive classification is a commonly used technique for categorising time-depth profiles of ...
Knowledge of the diving behaviour of aquatic animals expanded considerablywith the invention of time...
The behavior of many wild animals remains a mystery, as it is difficult to quantify behaviour of spe...
This file explains the variables in the acoustic telemetry detection dataset that accompanies: Kraus...
For diving animals, animal-borne sensors are used to collect time–depth information for studying beh...
To fulfill information gaps of underwater animal behavior, variety of animal-borne observation syste...
Abstract: Acceleration data loggers were attached to five adult Adelie penguins at Hukuro Cove, Lutz...
Acoustic positional telemetry systems (APTs) represent a novel approach to study the behaviour of fr...
Dive data collected from archival and satellite tags can provide valuable information on foraging ac...
Automatic algorithms for the detection and classification of sound are essential to the analysis of ...