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Found 7 papers, 1 papers with code
A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services
The insights and vision from this survey can be beneficial for the collaborative driving service development on low-power and memory-constrained systems and also for the energy optimization of autonomous vehicles.
SURIMI: Supervised Radio Map Augmentation with Deep Learning and a Generative Adversarial Network for Fingerprint-based Indoor Positioning
Indoor Positioning based on Machine Learning has drawn increasing attention both in the academy and the industry as meaningful information from the reference data can be extracted.
BIG-bench Machine Learning
Generative Adversarial Network
+1
Fault-Tolerant Collaborative Inference through the Edge-PRUNE Framework
Collaborative inference has received significant research interest in machine learning as a vehicle for distributing computation load, reducing latency, as well as addressing privacy preservation in communications.
Data Cleansing for Indoor Positioning Wi-Fi Fingerprinting Datasets
We use those to compute the correlation among all samples in the dataset and remove fingerprints with low level of correlation from the dataset.
Towards Accelerated Localization Performance Across Indoor Positioning Datasets
As a result, we bring forward the best-performing combination of models in terms of overall positioning accuracy and processing speed and evaluate on independent sets of samples.
Lightweight Hybrid CNN-ELM Model for Multi-building and Multi-floor Classification
Machine learning models have become an essential tool in current indoor positioning solutions, given their high capabilities to extract meaningful information from the environment.
Towards Ubiquitous Indoor Positioning: Comparing Systems across Heterogeneous Datasets
The evaluation of Indoor Positioning Systems (IPS) mostly relies on local deployments in the researchers' or partners' facilities.
