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Enhancing Supervised Terrain Classification with Predictive Unsupervised Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Variable Selection with Optimal Cell Damage
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Obstacle Detection and Terrain Classification for Autonomous Off-Road Navigation
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Fast and reliable obstacle detection and segmentation for cross-country navigation
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Combining laser range, color, and texture cues for autonomous road following
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Classifier fusion for outdoor obstacle detection
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Road detection and tracking for autonomous mobile robots
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Structural method for obstacle detection and terrain classification
inferredcites →https://doi.org/10.1177/0278364906065543openalex-snapshot
Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments
inferredcites →https://doi.org/10.1184/r1/6603146openalex-snapshot
ALVINN, an autonomous land vehicle in a neural network
inferredcites →https://doi.org/10.1535/itj.0902.03openalex-snapshot
Learning-Based Computer Vision with Intels Open Source Computer Vision Library
inferredcites →https://doi.org/10.15607/rss.2005.i.036openalex-snapshot
Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow
inferredcites →https://doi.org/10.48550/arxiv.1304.1098openalex-snapshot
Occupancy Grids: A Stochastic Spatial Representation for Active Robot Perception
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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