Vision-based semantic segmentation in scene understanding for autonomous driving: Recent achievements, challenges, and outlooks
Scene understanding plays a crucial role in autonomous driving by utilizing sensory data for
contextual information extraction and decision making. Beyond modeling advances, the …
contextual information extraction and decision making. Beyond modeling advances, the …
Wireless transmissions, propagation and channel modelling for iot technologies: Applications and challenges
The Internet of Things (IoT) has rapidly expanded for a wide range of applications towards a
smart future world by connecting everything. As a result, new challenges emerge in meeting …
smart future world by connecting everything. As a result, new challenges emerge in meeting …
[HTML][HTML] Large scale survey for radio propagation in developing machine learning model for path losses in communication systems
Several orthodox approaches, such as empirical methods and deterministic methods, had
earlier been used for the prediction of path loss in wireless communication systems. These …
earlier been used for the prediction of path loss in wireless communication systems. These …
EM DeepRay: An expedient, generalizable, and realistic data-driven indoor propagation model
Efficient and realistic indoor radio propagation modeling tools are inextricably intertwined
with the design and operation of next-generation wireless networks. Machine-learning (ML) …
with the design and operation of next-generation wireless networks. Machine-learning (ML) …
A deep learning network planner: Propagation modeling using real-world measurements and a 3D city model
In urban scenarios, network planning requires awareness of the notoriously complex
propagation environment by accounting for blocking, diffraction, and reflection on buildings …
propagation environment by accounting for blocking, diffraction, and reflection on buildings …
Improving path loss prediction using environmental feature extraction from satellite images: Hand-crafted vs. convolutional neural network
There is an increased exploration of the potential of wireless communication networks in the
automation of daily human tasks via the Internet of Things. Such implementations are only …
automation of daily human tasks via the Internet of Things. Such implementations are only …
Enhancing machine learning models for path loss prediction using image texture techniques
SP Sotiroudis, K Siakavara… - IEEE Antennas and …, 2021 - ieeexplore.ieee.org
The performance of machine learning (ML)-based path loss models relies heavily on the
data they use at their inputs. Feature engineering is, therefore, essential for the model's …
data they use at their inputs. Feature engineering is, therefore, essential for the model's …
Performance of path loss models over mid-band and high-band channels for 5G communication networks: A review
The rapid development of 5G communication networks has ushered in a new era of high-
speed, low-latency wireless connectivity, as well as the enabling of transformative …
speed, low-latency wireless connectivity, as well as the enabling of transformative …
Deep Learning for Path Loss Prediction at 7 GHz in Urban Environment
TT Nguyen, N Yoza-Mitsuishi, R Caromi - IEEE Access, 2023 - ieeexplore.ieee.org
In the spectrum sharing band, unlicensed devices are managed by automated frequency
coordination (AFC) systems to protect incumbent services from interference. Thus, it is …
coordination (AFC) systems to protect incumbent services from interference. Thus, it is …
Visualizations for universal deep-feature representations: survey and taxonomy
In data science and content-based retrieval, we find many domain-specific techniques that
employ a data processing pipeline with two fundamental steps. First, data entities are …
employ a data processing pipeline with two fundamental steps. First, data entities are …