[1]
|
Drones are an effective tool to assess the impact of feral horses in an alpine riparian environment
Austral Ecology,
2023
DOI:10.1111/aec.13271
|
|
|
[2]
|
Mobile Services for Smart Agriculture and Forestry, Biodiversity Monitoring, and Water Management: Challenges for 5G/6G Networks
Telecom,
2023
DOI:10.3390/telecom4010006
|
|
|
[3]
|
Drones are an effective tool to assess the impact of feral horses in an alpine riparian environment
Austral Ecology,
2023
DOI:10.1111/aec.13271
|
|
|
[4]
|
A robotic honeycomb for interaction with a honeybee colony
Science Robotics,
2023
DOI:10.1126/scirobotics.add7385
|
|
|
[5]
|
Nature-Robot Interaction
Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction,
2023
DOI:10.1145/3568294.3580034
|
|
|
[6]
|
Nature-Robot Interaction
Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction,
2023
DOI:10.1145/3568294.3580034
|
|
|
[7]
|
Handbook of Philosophy of Climate Change
Handbooks in Philosophy,
2023
DOI:10.1007/978-3-030-16960-2_117-1
|
|
|
[8]
|
Towards new ecologies of automation: Robotics and the re-engineering of nature
Geoforum,
2023
DOI:10.1016/j.geoforum.2023.103825
|
|
|
[9]
|
Recursive inverse dynamics of a swimming snake-like robot with a tree-like mechanical structure
2023 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO),
2023
DOI:10.1109/ARSO56563.2023.10187577
|
|
|
[10]
|
Handbook of the Philosophy of Climate Change
Handbooks in Philosophy,
2023
DOI:10.1007/978-3-031-07002-0_117
|
|
|
[11]
|
Smart Green Innovations in Industry 4.0
Springer Climate,
2023
DOI:10.1007/978-3-031-45830-9_15
|
|
|
[12]
|
A robotic honeycomb for interaction with a honeybee colony
Science Robotics,
2023
DOI:10.1126/scirobotics.add7385
|
|
|
[13]
|
Industry 4.0
2022
DOI:10.1007/978-3-030-79496-5_31
|
|
|
[14]
|
Comparison of drone vs. ground survey monitoring of hatching success in the black-headed gull (Chroicocephalus ridibundus)
Ornithology Research,
2022
DOI:10.1007/s43388-022-00112-2
|
|
|
[15]
|
Surveying cliff-nesting seabirds with unoccupied aircraft systems in the Gulf of Alaska
Polar Biology,
2022
DOI:10.1007/s00300-022-03101-9
|
|
|
[16]
|
Industry 4.0
2022
DOI:10.1007/978-3-030-79496-5_31
|
|
|
[17]
|
Social Integrating Robots Suggest Mitigation Strategies for Ecosystem Decay
Frontiers in Bioengineering and Biotechnology,
2021
DOI:10.3389/fbioe.2021.612605
|
|
|
[18]
|
Using an unmanned aerial system to monitor and assess irrigation water channels susceptible to sediment deposition
Environmental Monitoring and Assessment,
2021
DOI:10.1007/s10661-021-09313-6
|
|
|
[19]
|
Steps Toward an Ethics of Environmental Robotics
Philosophy & Technology,
2021
DOI:10.1007/s13347-020-00399-3
|
|
|
[20]
|
Advances in image acquisition and processing technologies transforming animal ecological studies
Ecological Informatics,
2021
DOI:10.1016/j.ecoinf.2021.101212
|
|
|
[21]
|
Advances in image acquisition and processing technologies transforming animal ecological studies
Ecological Informatics,
2021
DOI:10.1016/j.ecoinf.2021.101212
|
|
|
[22]
|
Drone-conducted counts as a tool for the rapid assessment of productivity of Sandwich Terns (Thalasseus sandvicensis)
Journal of Ornithology,
2021
DOI:10.1007/s10336-020-01854-w
|
|
|
[23]
|
Hydroacoustic Autonomous boat for Remote fish detection in
LakE (HARLE
), an unmanned autonomous surface vehicle to monitor fish populations in lakes
Limnology and Oceanography: Methods,
2021
DOI:10.1002/lom3.10422
|
|
|
[24]
|
Hydroacoustic Autonomous boat for Remote fish detection in LakE (HARLE), an unmanned autonomous surface vehicle to monitor fish populations in lakes
Limnology and Oceanography: Methods,
2021
DOI:10.1002/lom3.10422
|
|
|
[25]
|
Recent biological invasion shapes species recognition and aggressive behaviour in a native species: A behavioural experiment using robots in the field
Journal of Animal Ecology,
2020
DOI:10.1111/1365-2656.13223
|
|
|
[26]
|
Drones Improve Effectiveness and Reduce Disturbance of Censusing Common Redshanks Tringa totanus Breeding on Salt Marshes
Ardea,
2020
DOI:10.5253/arde.v107i3.a3
|
|
|
[27]
|
The Hierarchic Treatment of Marine Ecological Information from Spatial Networks of Benthic Platforms
Sensors,
2020
DOI:10.3390/s20061751
|
|
|
[28]
|
Recent biological invasion shapes species recognition and aggressive behaviour in a native species: A behavioural experiment using robots in the field
Journal of Animal Ecology,
2020
DOI:10.1111/1365-2656.13223
|
|
|
[29]
|
Artificial Intelligence Meets Citizen Science to Supercharge Ecological Monitoring
Patterns,
2020
DOI:10.1016/j.patter.2020.100109
|
|
|
[30]
|
Deep Learning for Inexpensive Image Classification of Wildlife on the Raspberry Pi
2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON),
2019
DOI:10.1109/UEMCON47517.2019.8993061
|
|
|
[31]
|
Drones for Conservation in Protected Areas: Present and Future
Drones,
2019
DOI:10.3390/drones3010010
|
|
|
[32]
|
Trends in drone research and applications as the Journal of Unmanned Vehicle Systems turns five
Journal of Unmanned Vehicle Systems,
2018
DOI:10.1139/juvs-2018-0005
|
|
|
[33]
|
New Vectorial Propulsion System and Trajectory Control Designs for Improved AUV Mission Autonomy
Sensors,
2018
DOI:10.3390/s18041241
|
|
|
[34]
|
Animal personality and behavioral syndromes in amphibians: a review of the evidence, experimental approaches, and implications for conservation
Behavioral Ecology and Sociobiology,
2018
DOI:10.1007/s00265-018-2493-7
|
|
|
[35]
|
Expert, Crowd, Students or Algorithm: who holds the key to deep-sea imagery ‘big data’ processing?
Methods in Ecology and Evolution,
2017
DOI:10.1111/2041-210X.12746
|
|
|
[36]
|
Monitoring butterflies with an unmanned aerial vehicle: current possibilities and future potentials
Journal of Ecology and Environment,
2017
DOI:10.1186/s41610-017-0028-1
|
|
|
[37]
|
The Dawning of the Ethics of Environmental Robots
Science and Engineering Ethics,
2017
DOI:10.1007/s11948-017-9990-3
|
|
|
[38]
|
Using unmanned aerial vehicles to sample aquatic ecosystems
Limnology and Oceanography: Methods,
2017
DOI:10.1002/lom3.10222
|
|
|
[39]
|
Seabird species vary in behavioural response to drone census
Scientific Reports,
2017
DOI:10.1038/s41598-017-18202-3
|
|
|
[40]
|
Expert, Crowd, Students or Algorithm: who holds the key to deep‐sea imagery ‘big data’ processing?
Methods in Ecology and Evolution,
2017
DOI:10.1111/2041-210X.12746
|
|
|
[41]
|
Seabird species vary in behavioural response to drone census
Scientific Reports,
2017
DOI:10.1038/s41598-017-18202-3
|
|
|
[42]
|
Using unmanned aerial vehicles to sample aquatic ecosystems
Limnology and Oceanography: Methods,
2017
DOI:10.1002/lom3.10222
|
|
|
[43]
|
Feasibility study and application of three-dimensional aerial photogrammetry technology using unmanned aerial vehicle (UAV) to natural environmental measurements.
Ecology and Civil Engineering,
2016
DOI:10.3825/ece.19.91
|
|
|
[44]
|
Reference Module in Earth Systems and Environmental Sciences
2016
DOI:10.1016/B978-0-12-409548-9.10418-X
|
|
|
[45]
|
UAV application in ecology: Data collecting with quad-copter equipped with Arduino based measurement platform
2016 International Symposium ELMAR,
2016
DOI:10.1109/ELMAR.2016.7731794
|
|
|
[46]
|
Approaching birds with drones: first experiments and ethical guidelines
Biology Letters,
2015
DOI:10.1098/rsbl.2014.0754
|
|
|
[47]
|
A small unmanned aerial system for estimating abundance and size of Antarctic predators
Polar Biology,
2015
DOI:10.1007/s00300-014-1625-4
|
|
|
[48]
|
The use of conservation drones in ecology and wildlife research
Journal of Ecology and Environment,
2015
DOI:10.5141/ecoenv.2015.012
|
|
|
[49]
|
Distance Sampling: Methods and Applications
Methods in Statistical Ecology,
2015
DOI:10.1007/978-3-319-19219-2_1
|
|
|
[50]
|
Distance Sampling: Methods and Applications
Methods in Statistical Ecology,
2015
DOI:10.1007/978-3-319-19219-2_12
|
|
|
[51]
|
Rovers minimize human disturbance in research on wild animals
Nature Methods,
2014
DOI:10.1038/nmeth.3173
|
|
|