0000000000010788

AUTHOR

Jeppe Have Rasmussen

0000-0003-3426-551x

showing 3 related works from this author

Applying Artificial Intelligence Methods to Detect and Classify Fish Calls from the Northern Gulf of Mexico

2021

Passive acoustic monitoring is a method that is commonly used to collect long-term data on soniferous animal presence and abundance. However, these large datasets require substantial effort for manual analysis

Point of interestComputer scienceneural networkNaval architecture. Shipbuilding. Marine engineeringVM1-989Ocean EngineeringGC1-1581OceanographyClassifier (linguistics)VDP::Matematikk og Naturvitenskap: 400::Basale biofag: 470VDP::Landbruks- og Fiskerifag: 900::Fiskerifag: 920Water Science and TechnologyCivil and Structural EngineeringGulf of MexicoRecallArtificial neural networkbusiness.industryDetectorfish call detectionfish soundsPattern recognitionenergy detectorartificial intelligenceVariable (computer science)classificationNoise (video)Artificial intelligencebusinessEnergy (signal processing)Journal of Marine Science and Engineering
researchProduct

Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook

2022

The deep learning revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. These new methods provide analysis of data from sensors, cameras, and acoustic recorders, even in real time, in ways that are reproducible and rapid. Off-the-shelf algorithms can find, count, and classify species from digital images or video and detect cryptic patterns in noisy data. Using these opportunities requires collaboration across ecological and data science disciplines, which can be challenging to initiate. To facilitate these collaborations and promote the use of deep learning towards ecosystem-based management…

FOS: Computer and information sciences0106 biological sciencesArtificial intelligenceComputer Science - Machine LearningEcologyComputer Science - Artificial IntelligenceComputer Vision and Pattern Recognition (cs.CV)010604 marine biology & hydrobiologyComputer Science - Computer Vision and Pattern RecognitionMarine monitoringMarine bioacousticsAquatic ScienceEcosystem-based managementOceanography010603 evolutionary biology01 natural sciencesMachine Learning (cs.LG)VDP::Teknologi: 500Artificial Intelligence (cs.AI)13. Climate actionMachine learning14. Life underwaterEcology Evolution Behavior and Systematics
researchProduct

FishSizer: Software solution for efficiently measuring larval fish size

2022

Length and depth of fish larvae are part of the fundamental measurements in many marine ecology studies involving early fish life history. Until now, obtaining these measurements has required intensive manual labor and the risk of inter- and intra-observer variability. We developed an open-source software solution to semi-automate the measurement process and thereby reduce both time consumption and technical variability. Using contrast-based edge detection, the software segments images of a fish larva into “larva” and “background.” Length and depth are extracted from the “larva” segmentation while taking curvature of the larva into consideration. The graphical user interface optimizes workf…

EcologyVDP::Matematikk og Naturvitenskap: 400::Basale biofag: 470Ecology Evolution Behavior and SystematicsNature and Landscape Conservation
researchProduct