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Deep Learning for Exploration and Recovery of Uncharted and Dynamic Targets from UAV-like Vision.

, , and . IROS, page 1124-1131. IEEE, (2018)

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Automatic individual holstein friesian cattle identification via selective local coat pattern matching in RGB-D imagery., , , and . ICIP, page 484-488. IEEE, (2016)Towards Self-Supervision for Video Identification of Individual Holstein-Friesian Cattle: The Cows2021 Dataset., , , , and . CoRR, (2021)Visual Localisation and Individual Identification of Holstein Friesian Cattle via Deep Learning., , and . ICCV Workshops, page 2850-2859. IEEE Computer Society, (2017)Aerial Animal Biometrics: Individual Friesian Cattle Recovery and Visual Identification via an Autonomous UAV with Onboard Deep Inference., , and . IROS, page 237-243. IEEE, (2019)Deep Learning for Exploration and Recovery of Uncharted and Dynamic Targets from UAV-like Vision., , and . IROS, page 1124-1131. IEEE, (2018)Universal Bovine Identification via Depth Data and Deep Metric Learning., , , , , , , , , and . CoRR, (2024)Fusing Animal Biometrics with Autonomous Robotics: Drone-based Search and Individual ID of Friesian Cattle (Extended Abstract)., , and . WACV Workshops, page 38-43. IEEE, (2020)Defining gaze tracking metrics by observing a growing divide between 2D and 3D tracking., , , and . HVEI, Society for Imaging Science and Technology, (2020)To report or not to report? Extending Protection Motivation Theory to Vulnerability Discovery and Disclosure., , and . Comput. Secur., (2024)Demo: Efficient delay and apodization for on-FPGA 3D ultrasound., , , , , , and . DASIP, page 227-228. IEEE, (2016)