Results 151 to 160 of about 4,939 (248)

Comparison of Conventional, Rake, and Sonar‐Based Biophysical Habitat Measurements in a Shallow Ontario River

River Research and Applications, EarlyView.
ABSTRACT Knowledge of habitat availability is critically important for the management and recovery of freshwater species. Quantifying habitat availability often requires fine‐scale sampling at point‐based locations across a large geographic extent, which can be laboursome.
Karl A. Lamothe, Jason Barnucz, D. Andrew R. Drake   +2 more
wiley   +1 more source

SeADL: Self-Adaptive Deep Learning for Real-Time Marine Visibility Forecasting Using Multi-Source Sensor Data. [PDF]

Sensors (Basel)
Girard W, Xu H, Yan D.
europepmc   +1 more source

Comparing convolutional neural network and random forest for benthic habitat mapping in Apollo Marine Park

Remote Sensing in Ecology and Conservation, EarlyView.
A comparison of Convolutional Neural Network (CNN) and Random Forest (RF) model predictions of benthic habitats within Apollo Marine Park. The CNN (left) and RF (right) classification maps show the spatial distribution of three habitat types: high energy circalittoral rock with seabed‐covering sponges, low complexity circalittoral rock with non‐crowded
Henry Simmons, Dang Nguyen, Benjamin Misiuk, Daniel Ierodiaconou, Sunil Gupta, Oli Dalby, Mary Young   +6 more
wiley   +1 more source

Tracing the geopolitical influences on the morphological and functional transformation in Guangdong merchant ships: Knowledge mining from the Ming and Qing maritime archives. [PDF]

PLoS One
Ao J, Zhao M, Li W, Feng S, Ye Z, Xu Z, Ji S.   +6 more
europepmc   +1 more source

Programmed unmanned aerial vehicles show great potential for monitoring marine megafauna in specific areas of interest

Remote Sensing in Ecology and Conservation, EarlyView.
Targeted conservation measures are contingent on robust knowledge of spatio‐temporal animal distribution in areas of interest. We explore unmanned aerial vehicle (UAV) transect monitoring as a novel method for standardized digital aerial surveys of marine megafauna by investigating the fine‐resolution spatio‐temporal distribution of harbour porpoises ...
Dinah Hartmann, Valdemar Palmqvist, Johanna Stedt   +2 more
wiley   +1 more source

Intelligent ship traffic supervision system based on distributed blockchain and federated reinforcement learning for collaborative decision optimization. [PDF]

Sci Rep
Wei Z, Rongjun P, Shijie W, Meiqing C.
europepmc   +1 more source

Incorporating environmental DNA metabarcoding for improved benthic biodiversity and habitat mapping

Remote Sensing in Ecology and Conservation, EarlyView.
Seafloor imagery is commonly used to collect information about the distribution of benthic organisms in order to generate habitat and biodiversity maps. Recent advances in genomics (e.g., environmental DNA; eDNA) show potential to complement video surveys for habitat mapping, but there have been few examples testing this.
Rylan J. Command, Shreya Nemani, Benjamin Misiuk, Mehrdad Hajibabaei, Nicole Fahner, Emily Porter, Greg Singer, Beverly McClenaghan, Katleen Robert   +8 more
wiley   +1 more source

Evaluating Emotional Response and Effort in Nautical Simulation Training Using Noninvasive Methods. [PDF]

Sensors (Basel)
Žagar D.
europepmc   +1 more source

Semi‐automated seal detection on the Western Antarctic Peninsula: an unsupervised machine learning approach for detecting ice seals in aerial survey data

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a semi‐automated, rule‐based image analysis pipeline to detect ice seals in aerial surveys of the Western Antarctic Peninsula during an unusually low sea ice year. By using simple hierarchical clustering instead of deep learning, the method substantially reduced human annotation effort while achieving 82% recall, identifying 758 ...
Claire McGinnity, Connor C.G. Bamford, Nathan Fenney, Andrew Fleming, Jaume Forcada, Michael S. Tift, Luis A. Hückstädt, Daniel P. Costa, Peter T. Fretwell   +8 more
wiley   +1 more source

High-Precision Marine Radar Object Detection Using Tiled Training and SAHI Enhanced YOLOv11-OBB. [PDF]

Sensors (Basel)
Külcü S.
europepmc   +1 more source