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Found 12 papers, 1 papers with code
EMP: Enhance Memory in Data Pruning
Finally, we propose Enhance Memory Pruning (EMP), which addresses the issue of insufficient memory under high pruning rates by enhancing the model's memory of data, thereby improving its performance.
SGP-RI: A Real-Time-Trainable and Decentralized IoT Indoor Localization Model Based on Sparse Gaussian Process with Reduced-Dimensional Inputs
This centralized approach faces several challenges, including the database's inability to accommodate the dynamic and unpredictable nature of the indoor electromagnetic environment, the model retraining costs, and the susceptibility of centralized servers to security breaches.
Mean Teacher based SSL Framework for Indoor Localization Using Wi-Fi RSSI Fingerprinting
Wi-Fi fingerprinting is widely applied for indoor localization due to the widespread availability of Wi-Fi devices.
Hierarchical Stage-Wise Training of Linked Deep Neural Networks for Multi-Building and Multi-Floor Indoor Localization Based on Wi-Fi RSSI Fingerprinting
In this paper, we present a new solution to the problem of large-scale multi-building and multi-floor indoor localization based on linked neural networks, where each neural network is dedicated to a sub-problem and trained under a hierarchical stage-wise training framework.
LNPT: Label-free Network Pruning and Training
Pruning before training enables the deployment of neural networks on smart devices.
SEVEN: Pruning Transformer Model by Reserving Sentinels
We utilize this design to dynamically assess the importance scores of weights. SEVEN is introduced by us, which particularly favors weights with consistently high sensitivity, i. e., weights with small gradient noise.
Static vs. Dynamic Databases for Indoor Localization based on Wi-Fi Fingerprinting: A Discussion from a Data Perspective
As a case study, we have constructed a dynamic database covering three floors of the IR building of XJTLU based on RSSI measurements, over 44 days, and investigated the differences between static and dynamic databases in terms of statistical characteristics and localization performance.
On the Multidimensional Augmentation of Fingerprint Data for Indoor Localization in A Large-Scale Building Complex Based on Multi-Output Gaussian Process
Wi-Fi fingerprinting becomes a dominant solution for large-scale indoor localization due to its major advantage of not requiring new infrastructure and dedicated devices.
Multi-Output Gaussian Process-Based Data Augmentation for Multi-Building and Multi-Floor Indoor Localization
Location fingerprinting based on RSSI becomes a mainstream indoor localization technique due to its advantage of not requiring the installation of new infrastructure and the modification of existing devices, especially given the prevalence of Wi-Fi-enabled devices and the ubiquitous Wi-Fi access in modern buildings.
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance.
A differential evolution-based optimization tool for interplanetary transfer trajectory design
As a representative, the current known best solution of the global trajectory optimization problem (GTOP) designed by the European space agency (ESA) is very hard to be found.
XJTLUIndoorLoc: A New Fingerprinting Database for Indoor Localization and Trajectory Estimation Based on Wi-Fi RSS and Geomagnetic Field
In this paper, we present a new location fingerprinting database comprised of Wi-Fi received signal strength (RSS) and geomagnetic field intensity measured with multiple devices at a multi-floor building in Xi'an Jiatong-Liverpool University, Suzhou, China.
