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Found 6 papers, 0 papers with code
Precision in Building Extraction: Comparing Shallow and Deep Models using LiDAR Data
This article targets shallow models due to their interpretable nature to assess the presence of LiDAR data for supervised segmentation.
Self-supervised Hypergraphs for Learning Multiple World Interpretations
Thus, each node could be an input node in some hyperedges and an output node in others.
Saliency Can Be All You Need In Contrastive Self-Supervised Learning
We propose an augmentation policy for Contrastive Self-Supervised Learning (SSL) in the form of an already established Salient Image Segmentation technique entitled Global Contrast based Salient Region Detection.
The Vision of Self-Evolving Computing Systems
We motivate the need for self-evolving computing systems in light of the state of the art, outline a conceptual architecture of self-evolving computing systems, and illustrate the architecture for a future smart city mobility system that needs to evolve continuously with changing conditions.
Lifelong Computing
When detecting anomalies, novelties, new goals or constraints, a lifelong computing system activates an evolutionary self-learning engine that runs online experiments to determine how the computing-learning system needs to evolve to deal with the changes, thereby changing its architecture and integrating new computing elements from computing warehouses as needed.
Event-Driven Stereo Matching for Real-Time 3D Panoramic Vision
This paper presents a stereo matching approach for a novel multi-perspective panoramic stereo vision system, making use of asynchronous and non-simultaneous stereo imaging towards real-time 3D 360deg vision.
