A survey on hyperdimensional computing aka vector symbolic architectures, part ii: Applications, cognitive models, and challenges
This is Part II of the two-part comprehensive survey devoted to a computing framework most
commonly known under the names Hyperdimensional Computing and Vector Symbolic …
commonly known under the names Hyperdimensional Computing and Vector Symbolic …
Hyperseed: Unsupervised learning with vector symbolic architectures
Motivated by recent innovations in biologically inspired neuromorphic hardware, this article
presents a novel unsupervised machine learning algorithm named Hyperseed that draws on …
presents a novel unsupervised machine learning algorithm named Hyperseed that draws on …
Multivariate time series analysis for driving style classification using neural networks and hyperdimensional computing
In this paper, we present a novel approach for driving style classification based on time
series data. Instead of automatically learning the embedding vector for temporal …
series data. Instead of automatically learning the embedding vector for temporal …
Improving Efficiency and Generalisability of Motion Predictions With Deep Multi-Agent Learning and Multi-Head Attention
Automated Vehicles (AVs) have been receiving increasing attention as a potential highly
mechanised, intelligent, self-regulating futuristic mode of transport. AVs are predicted to …
mechanised, intelligent, self-regulating futuristic mode of transport. AVs are predicted to …
Real‐Time Vehicle Trajectory Prediction for Traffic Conflict Detection at Unsignalized Intersections
Q Cao, Z Zhao, Q Zeng, Z Wang… - Journal of advanced …, 2021 - Wiley Online Library
Real‐time prediction of vehicle trajectory at unsignalized intersections is important for real‐
time traffic conflict detection and early warning to improve traffic safety at unsignalized …
time traffic conflict detection and early warning to improve traffic safety at unsignalized …
Vehicle behavior prediction and generalization using imbalanced learning techniques
The use of learning-based methods for vehicle behavior prediction is a promising research
topic. However, many publicly available data sets suffer from class distribution skews which …
topic. However, many publicly available data sets suffer from class distribution skews which …
Beyond the Data Imbalance: Employing the Heterogeneous Datasets for Vehicle Maneuver Prediction
Predicting the maneuvers of surrounding vehicles is imperative for the safe navigation of
autonomous vehicles. However, naturalistic driving datasets tend to be highly imbalanced …
autonomous vehicles. However, naturalistic driving datasets tend to be highly imbalanced …
Round goby [Neogobius melanostomus (Pallas, 1814)], gudgeon (Gobio gobio L.) and bullhead (Cottus gobio L.) show distinct swimming patterns in a vertical slot …
The vertical slots of fish passes represent bottlenecks that must be passed by every fish
migrating upstream. The hydraulics in fish passes are well investigated but less is known …
migrating upstream. The hydraulics in fish passes are well investigated but less is known …
Enhancing Neural Spoken Language Recognition: An Exploration with Multilingual Datasets
OH Anidjar, R Yozevitch - arXiv preprint arXiv:2501.11065, 2025 - arxiv.org
In this research, we advanced a spoken language recognition system, moving beyond
traditional feature vector-based models. Our improvements focused on effectively capturing …
traditional feature vector-based models. Our improvements focused on effectively capturing …
Automatic detection of fake tweets about the COVID-19 Vaccine in Portuguese
R Geurgas, LR Tessler - Social Network Analysis and Mining, 2024 - Springer
The COVID-19 pandemic induced an unprecedented wave of disinformation in social media
in Brazil. In particular, Twitter (currently X) was used to spread fake news about COVID-19 …
in Brazil. In particular, Twitter (currently X) was used to spread fake news about COVID-19 …