Sökning: "depth sensors"

Visar resultat 11 - 15 av 92 uppsatser innehållade orden depth sensors.

  1. 11. Identification and strength classification of weakness zones in the Garpenberg mine based on measurement while drilling (MWD)

    Master-uppsats, Luleå tekniska universitet/Geoteknologi

    Författare :Ioannis Peroulakis; [2022]
    Nyckelord :Drilling; MWD; Garpenberg; Mining; Geotechnics;

    Sammanfattning : Boliden’s Garpenberg mine produces Zn-Pb-Ag(Cu-Au) using a sublevel stoping with pastefill mining method. The orebody is strongly affected by the existence of weakness zones mainly consisting of Talc Schist and Phlogopite Schist which affect the design, planning and production of the stope. LÄS MER

  3. 12. Determining Anomalies in Radar Data for Seedbed Tine Harrow Operation

    Master-uppsats, Linköpings universitet/Institutionen för systemteknik

    Författare :William Winbladh; Karl Persson; [2022]
    Nyckelord :Machine learning; Diagnostics; Harrowing; Seedbed tine harrow; Radar; Ada-boost; Random forest; SVM;

    Sammanfattning : The agricultural industry is constantly evolving with automation as one of the current main focuses. This thesis involves the automation of a seedbed tine harrow, specifically the control of the tillage depth. LÄS MER

  4. 13. CNN-Based Methods for Tree Species Detection in UAV Images

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Olle Sievers; [2022]
    Nyckelord :Machine Learning; CNN; UAV; Tree Species; Deep Learning; Tree Species Detection; Detection;

    Sammanfattning : Unmanned aerial vehicles (UAVs) with high-resolution cameras are common in today’s society. Industries, such as the forestry industry, use drones to get a fast overview of tree populations. LÄS MER

  5. 14. RGB-D Deep Learning keypoints and descriptors extraction Network for feature-based Visual Odometry systems

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Federico Bennasciutti; [2022]
    Nyckelord :DeepLearning; Visual Odometry; Computer Vision; RGB-D Camera; Feature Extraction; Interest Point Extraction; Djupinlärning; Visuell Odometri; Datorseende; RGB-D-kamera; Nyckelpunkter; Detektion;

    Sammanfattning : Feature extractors in Visual Odometry pipelines rarely exploit depth signals, even though depth sensors and RGB-D cameras are commonly used in later stages of Visual Odometry systems. Nonetheless, depth sensors from RGB-D cameras function even with no external light and can provide feature extractors with additional structural information otherwise invisible in RGB images. LÄS MER

  7. 15. Characterizing Pose Uncertainty in Semantic Perception Pipelines : Leveraging semantic information to improve path planning in dynamic environments

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Thomas Labourdette-Liaresq; [2022]
    Nyckelord :;

    Sammanfattning : Mobile robots possess complex perception pipelines composed of visual and depth sensors which allow them to understand their location and the world around them and build models of this world. Real-time motion planning of mobile robots in complex environments requires the knowledge of the properties of the perception pipeline so that accurate, robust and safe robot operations can be performed. LÄS MER