Results 241 to 250 of about 2,799,679 (274)

Nearest Neighbour Classification for Trajectory Data

2010
Trajectory data mining is an emerging area of research, having a large variety of applications. This paper proposes a nearest neighbour based trajectory data as two-step process. Extensive experiments were conducted using real datasets of moving vehicles in Milan (Italy).
Lokesh Kumar Sharma, Om Prakash Vyas, Simon Scheider, Ajaya K. Akasapu   +3 more
openaire   +2 more sources

Classification of trajectories—Extracting invariants with a neural network

Neural Networks, 1993
A neural classifier of planar trajectories is presented. There already exist a large variety of classifiers that are specialized in particular invariants contained in a trajectory classification task such as position-invariance, rotation-invariance, and size-invariance.
Margit Kinder, Wilfried Brauer
openaire   +2 more sources

Transformer Networks for Trajectory Classification

2022 IEEE International Conference on Big Data and Smart Computing (BigComp), 2022
Keywoong Bae, Suan Lee, Wookey Lee
openaire   +1 more source

Locality-Constrained Sparse Reconstruction for Trajectory Classification

2014 22nd International Conference on Pattern Recognition, 2014
Trajectory classification has been extensively investigated in recent years, however, problems remain when processing incomplete trajectories of noises and local variations. In this paper, we propose a Locality-constrained Sparse Reconstruction (LSR) approach that explores both sparsity and local adaptability for robust trajectory classification.
Ce Li 0005, Zhenjun Han, Qixiang Ye, Shan Gao 0003, Lijin Pang, Jianbin Jiao   +5 more
openaire   +2 more sources

Stop consonant classification by dynamic formant trajectory

Interspeech 2004, 2004
LPC analysis is one of the most powerful techniques in speech analysis. Spectral zeros during consonant or consonant-vowel transition regions introduce difficulties in estimating LPC parameters. In this paper, we propose to estimate formant frequencies from LPC model by MUSIC (Multiple Signal Classification) and ESPRIT (Estimation of Signal Parameters ...
Yanli Zheng, Mark Hasegawa-Johnson, Sarah Borys   +2 more
openaire   +2 more sources

Optimal Trajectories for Cooperative Classification

2003
A projected role for autonomous uninhabited air vehicles is to classify and subsequently attack time critical targets, as well as perform battle damage assessment after an attack. Thus, the problem of determining optimal look angles for automatic target recognition/classification is addressed first. Next, minimum time trajectories for this mission, for
Meir Pachter, Jeffrey Hebert
openaire   +1 more source

Weightless neuro-symbolic GPS trajectory classification

Neurocomputing, 2018
Abstract This paper presents a framework for dealing with the problem of GPS trajectory classification in the context of the Rio de Janeiro’s public transit system (with hundreds or more classes). Such framework combines the versatile WiSARD classifier with a set of rules defined a priori, resulting in a neuro-symbolic learning system with very ...
Raul Barbosa, Douglas de O. Cardoso, Diego Carvalho 0001, Felipe M. G. França   +3 more
openaire   +2 more sources

Hyperparameters of Gaussian process as features for trajectory classification

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008
In this paper, we address the trajectory classification problem in Gaussian process framework without using Gaussian process based classification directly. Properties of the function corresponding to a trajectory are captured into the hyperparameters of a Gaussian process.
G. Haranadh, C. Chandra Sekhar
openaire   +2 more sources

TrajFormer: Efficient Trajectory Classification with Transformers

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Yuxuan Liang 0002, Kun Ouyang, Yiwei Wang 0001, Xu Liu 0014, Hongyang Chen 0001, Junbo Zhang 0004, Yu Zheng 0004, Roger Zimmermann   +7 more
openaire   +1 more source

Probabilistic Semantic Classification of Trajectories

2010
The approaches described in previous chapters are able to classify static observations using a mobile robot. However, mobile robots are dynamic agents that move along different trajectories. When operating in indoor environments, robots usually have a moderate velocity and a relatively continuous movement.
openaire   +1 more source