Results 101 to 110 of about 101,715 (197)

Ubiquitous sensing of marine activities via the cooperation of autonomous underwater vehicles. [PDF]

Sci Rep
Yan J, Jiang Y, Wang X, Yu J, Yang X, Chen C, Guan X.   +6 more
europepmc   +1 more source

YOLO-MFD: a multi-scale feature and dynamic head framework for prefabricated shoreline underwater object detection. [PDF]

Sci Rep
Gang Y, Li T, Li S, Shang Y.
europepmc   +1 more source

A waterproof and ultra-elastic thermoelectric foam for underwater human signal detection. [PDF]

Nat Commun
Liu W, Shi XL, He X, Zhu S, Li Z, Li C, Zhang D, Li M, Wu X, Zhang H, Wang L, Qin X, Chen ZG.   +12 more
europepmc   +1 more source

A comparative performance evaluation of distributed collision-free MAC protocols for underwater sensor networks [PDF]

, 2019
Alfouzan, Faisal, Boutaleb, Tuleen, Ghoreyshi, Seyed Mohammad, Shahrabi, Alireza   +3 more
core   +1 more source

Design and Development of a Sensor-Enhanced Remotely Operated Underwater Vehicle (ROUV) Platform for Environmental Monitoring. [PDF]

Sensors (Basel)
Tziourtzioumis D, Minos G, Anagnostaki T, Kenanidis E, Kosmanis T.   +4 more
europepmc   +1 more source

A novel augmented reality and reinforcement learning empowered communication framework for underwater unmanned autonomous vehicle. [PDF]

Sci Rep
Lakhan A, Mohammed MA, Ghani MKA, Memon S, Khan S, Marhoon HA, Radhi AD, Martinek R.   +7 more
europepmc   +1 more source

Collision risks between marine renewable energy devices and mammals, fish and diving birds: report to the Scottish Executive [PDF]

, 2006
Batty, R.S., Carter, C., Daunt, F., Wilson, B.   +3 more
core  

Integrated carbon nanotube-reinforced PTFE nanofiber membranes for breathable, super-hydrophobic, and thermally resilient triboelectric nanogenerators. [PDF]

Adv Compos Hybrid Mater
Wang Y, Dong L.
europepmc   +1 more source

Innovation below the surface: development of a canine underwater search training device for submerged scent detection. [PDF]

Front Vet Sci
Bunker P, Brewster C.
europepmc   +1 more source

Deep Reinforcement Learning for Autonomous Underwater Navigation: A Comparative Study with DWA and Digital Twin Validation. [PDF]

Sensors (Basel)
Mari Z, Nawaf MM, Drap P.
europepmc   +1 more source