In my childhood, the movieSpy Kidswas one of my favorite things to watch on television. Seeing kids of my age using futuristic gadgets to save the world and win the day might have been a common trope, but it still was fun to watch. Amongst things like Jetpacks and self-driving cars,...
Based on the outcome of the earlier research, the main objectives of this study are: (a) to propose a novel methodology for the CRC monitoring by using a semiautomated fuzzy OBIA and as well as compering its efficiency against the two well-known pixel based machine learning techniques (SVM...
In the age of cheap drones and (close to) affordable satellite launches, there has never been that much data of our world from above. There are already companies using satellite imagery from companies likePlanetandDescartes Labs, applying object detection to count cars, trees and ships. This ha...
detection and yield estimation Sensors, 21 (1) (2020), p. 118, 10.3390/s21010118 Google Scholar Wu et al., 2018 M. Wu, W. Xie, X. Shi, P. Shao, Z. Shi Real-time drone detection using deep learning approach Proceedings of the international conference on machine learning and ...
These works lever- age various routes, including reinforcement learning [13], imitation learning [44], and supervised learning [5] with 3D scene representation, such as mesh, dense grids. How- ever, most of these 3D-aware embodied AI tasks only per-...
A workable, robust classifier using machine learning and data mining techniques is needed. Specifically, the approach should determine which features, or attributes (columns) are important; generate a multiplicity of classifiers; be robust; and be computationally appropriate for real world problem solving...
1. Finally, we try to combine distillation loss with imitation loss (denoted as 0.25-ID), but the performance is worse than only using imitation term, implying high level feature imitation and distillation on model outputs have very divergent objectives. 4.3. Imitation...
pre-process the datasets using Histogram of Oriented Gradients methods or smoothing filters to overcome a specific classification problem. Additionally, the detection of the Earth’s features is largely carried out at the pixel level in machine learning-based approaches24. Since landforms are ...
The neural mechanisms underlying conscious recognition remain unclear, particularly the roles played by the prefrontal cortex, deactivated brain areas and subcortical regions. We investigated neural activity during conscious object recognition using 7 Te
Machine learning 45(1) (2001) 17. Tjaden, H., Schwanecke, U., Sch¨omer, E.: Real-time monocular pose estimation of 3D objects using temporally consistent local color histograms. In: IEEE Conference on Computer Vision and Pattern Recognition. (2017) 16 Mathieu Garon, Denis Laurendeau and ...