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The objective of this study is to investigate spatial structures of error in the assessment of continuous raster data. The use of conventional diagnostics of error often overlooks the possible spatial variation in error because such…

Applications · Statistics 2025-10-15 Narumasa Tsutsumida , Pedro Rodríguez-Veiga , Paul Harris , Heiko Balzter , Alexis Comber

Making informed driving decisions requires reliable prediction of other vehicles' trajectories. In this paper, we present a novel learned multi-modal trajectory prediction architecture for automated driving. It achieves kinematically…

Robotics · Computer Science 2021-09-22 Faris Janjoš , Maxim Dolgov , J. Marius Zöllner

Accident prediction and timely preventive actions improve road safety by reducing the risk of injury to road users and minimizing property damage. Hence, they are critical components of advanced driver assistance systems (ADAS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Vipooshan Vipulananthan , Kumudu Mohottala , Kavindu Chinthana , Nimsara Paramulla , Charith D Chitraranjan

Long-term slow-slip events (LSSEs) usually occur on the deep, shallow parts of subducting plates and have substantial relation with adjacent megathrust fault motion. Conventional techniques of quantifying slow earthquake frictional features…

Geophysics · Physics 2022-09-21 Shin-ichi Ito , Masayuki Kano , Hiromichi Nagao

Gait recognition is a biometric technology that has received extensive attention. Most existing gait recognition algorithms are unimodal, and a few multimodal gait recognition algorithms perform multimodal fusion only once. None of these…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Shinan Zou , Jianbo Xiong , Chao Fan , Shiqi Yu , Jin Tang

Traffic forecasting in cellular networks is a challenging spatiotemporal prediction problem due to strong temporal dependencies, spatial heterogeneity across cells, and the need for scalability to large network deployments. Traditional…

Machine Learning · Computer Science 2026-03-16 Zineddine Bettouche , Khalid Ali , Andreas Fischer , Andreas Kassler

Landslides, movement of soil and rock under the influence of gravity, are common phenomena that cause significant human and economic losses every year. Experts use heterogeneous features such as slope, elevation, land cover, lithology, rock…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Ainaz Hajimoradlou , Gioachino Roberti , David Poole

Accurate vehicle trajectory prediction is essential for ensuring safety and efficiency in fully autonomous driving systems. While existing methods primarily focus on modeling observed motion patterns and interactions with other vehicles,…

Machine Learning · Computer Science 2025-07-15 Xinyi Ning , Zilin Bian , Dachuan Zuo , Semiha Ergan

The pedestrian trajectory prediction task is an essential component of intelligent systems. Its applications include but are not limited to autonomous driving, robot navigation, and anomaly detection of monitoring systems. Due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-07-28 Rongqin Liang , Yuanman Li , Jiantao Zhou , Xia Li

Over the last two decades, strain and GPS measurements have shown that slow slip on earthquake faults is a widespread phenomenon. Slow slip is also inferred from correlated small amplitude seismic signals known as nonvolcanic tremor and low…

The aim of this paper is to propose a 2D computational algorithm for modeling of the trigger and the propagation of shallow landslides caused by rainfall. We used a Molecular Dynamics (MD) inspired model, similar to discrete element method…

Geophysics · Physics 2015-06-11 Gianluca Martelloni , Franco Bagnoli , Emanuele Massaro

Slow slip events (SSEs) originate from a slow slippage on faults that lasts from a few days to years. A systematic and complete mapping of SSEs is key to characterizing the slip spectrum and understanding its link with coeval seismological…

Spatial data are often derived from multiple sources (e.g. satellites, in-situ sensors, survey samples) with different supports, but associated with the same properties of a spatial phenomenon of interest. It is common for predictors to…

To identify emerging microscopic structures in low temperature spin glasses, we study self-sustained clusters (SSC) in spin models defined on sparse random graphs. A message-passing algorithm is developed to determine the probability of…

Disordered Systems and Neural Networks · Physics 2018-07-04 Jacopo Rocchi , David Saad , Chi Ho Yeung

Fault-slip rockbursts, triggered by seismic rupture of nearby or remote faults, constitute a significant geohazard during deep underground excavations. Although these events occur frequently in underground projects, their underlying…

Geophysics · Physics 2025-09-10 Wenbo Pan , Zixin Zhang , Qinghua Lei

Crashworthiness assessment is a critical aspect of automotive design, traditionally relying on high-fidelity finite element (FE) simulations that are computationally expensive and time-consuming. This work presents an exploratory…

Machine Learning · Computer Science 2025-11-04 Mohammad Amin Nabian , Sudeep Chavare , Deepak Akhare , Rishikesh Ranade , Ram Cherukuri , Srinivas Tadepalli

Various complex water management decisions are made in snow-dominant watersheds with the knowledge of Snow-Water Equivalent (SWE) -- a key measure widely used to estimate the water content of a snowpack. However, forecasting SWE is…

We consider a sheared granular system experiencing intermittent dynamics of stick-slip type via discrete element simulations. The considered setup consists of a two-dimensional system of soft frictional particles sandwiched between solid…

Soft Condensed Matter · Physics 2023-05-24 Philip Bretz , Lou Kondic , Miro Kramar

Geohazards such as landslides have caused great losses to the safety of people's lives and property, which is often accompanied with surface cracks. If such surface cracks could be identified in time, it is of great significance for the…

Computer Vision and Pattern Recognition · Computer Science 2021-12-03 Yuting Yang , Gang Mei

In an intelligent transportation system, the key problem of traffic forecasting is how to extract periodic temporal dependencies and complex spatial correlations. Current state-of-the-art methods for predicting traffic flow are based on…

Machine Learning · Computer Science 2022-03-01 Zichuan Liu , Rui Zhang , Chen Wang , Zhu Xiao , Hongbo Jiang