DarLoc: Deep learning and data-feature augmentation based robust magnetic indoor localization
Magnetic-based indoor localization has attracted considerable attention due to the
pervasiveness of geomagnetic fields and is free of extra infrastructures. However, existing …
pervasiveness of geomagnetic fields and is free of extra infrastructures. However, existing …
A survey of machine learning in pedestrian localization systems: Applications, open issues and challenges
With the popularization of machine learning (ML) techniques and the increased chipset's
performance, the application of ML to pedestrian localization systems has received …
performance, the application of ML to pedestrian localization systems has received …
Survey of machine learning methods applied to urban mobility
To increase the sustainability in urban mobility, it is necessary to optimally combine public
and shared vehicles throughout a passenger's trip. In this work, we present a survey on …
and shared vehicles throughout a passenger's trip. In this work, we present a survey on …
Sensor-fusion for smartphone location tracking using hybrid multimodal deep neural networks
Many engineered approaches have been proposed over the years for solving the hard
problem of performing indoor localization using smartphone sensors. However, specialising …
problem of performing indoor localization using smartphone sensors. However, specialising …
SGANFuzz: A Deep Learning-Based MQTT Fuzzing Method Using Generative Adversarial Networks
As the Internet of Things (IoT) industry grows, the risk of network protocol security threats has
also increased. One protocol that has come under scrutiny for its security vulnerabilities is …
also increased. One protocol that has come under scrutiny for its security vulnerabilities is …