Sökning: "Faster region-based convolutional neural networks"
Hittade 4 uppsatser innehållade orden Faster region-based convolutional neural networks.
1. Reliable Detection of Water Areas in Multispectral Drone Imagery : A faster region-based CNN model for accurately identifying the location of small-scale standing water bodies
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Dengue and Zika are two arboviral viruses that affect a significant portion of the world population. The principal vector species of both viruses are Aedes aegypti and Aedes albopictus mosquitoes. They breed in very slow flowing or standing pools of water. LÄS MER
2. Autonomously docking, using object detection, and path planning
Master-uppsats, KTH/MekatronikSammanfattning : With today’s climate change Volvo Construction Equipment (CE) must develop machines that emit less carbon dioxide or no carbon dioxide at all. One way to go is to electrify their machines. Volvo CE has developed an autonomous electric machine called HX02. Today the HX02 is charged with an inverted pantograph. LÄS MER
3. Comparison of Player Tracking-by-Detection Algorithms in Football Videos
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In recent years, increasing demands on sports analytics have triggered growing research interest in automatic player tracking-by-detection approaches. Two prominent branches in this area are Convolutional Neural Network (CNN)-based visual object detectors and histogram-based detectors. LÄS MER
4. Region Proposal Based Object Detectors Integrated With an Extended Kalman Filter for a Robust Detect-Tracking Algorithm
Master-uppsats, Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)Sammanfattning : In this thesis we present a detect-tracking algorithm (see figure 3.1) that combines the detection robustness of static region proposal based object detectors, like the faster region convolutional neural network (R-CNN) and the region-based fully convolutional networks (R-FCN) model, with the tracking prediction strength of extended Kalman filters, by using, what we have called, a translating and non-rigid user input region of interest (RoI-) mapping. LÄS MER