DeepPaSTL: Spatio-temporal deep learning methods for predicting long-term pasture terrains using synthetic datasets
Effective management of dairy farms requires an accurate prediction of pasture biomass.
Generally, estimation of pasture biomass requires site-specific data, or often perfect world …
Generally, estimation of pasture biomass requires site-specific data, or often perfect world …
CAST: A convolutional attention spatiotemporal network for predictive learning
F Sun, W Jin - Applied Intelligence, 2023 - Springer
Predictive learning is receiving growing interests with wide applications. Combining RNN
and CNN, recent works attempt to capture temporal dependencies and spatial correlations …
and CNN, recent works attempt to capture temporal dependencies and spatial correlations …
Explaining intelligent agent's future motion on basis of vocabulary learning with human goal inference
Intelligent agents (IAs) that use machine learning for decision-making often lack the
explainability about what they are going to do, which makes human-IA collaboration …
explainability about what they are going to do, which makes human-IA collaboration …
[PDF][PDF] Sequential forecasting of 100,000 points
Predicting the future is a crucial first step to effective control, since systems that can predict
the future can select plans that lead to desired outcomes. In this work, we study the problem …
the future can select plans that lead to desired outcomes. In this work, we study the problem …
Diverse video generation using a gaussian process trigger
G Shrivastava, A Shrivastava - arXiv preprint arXiv:2107.04619, 2021 - arxiv.org
Generating future frames given a few context (or past) frames is a challenging task. It
requires modeling the temporal coherence of videos and multi-modality in terms of diversity …
requires modeling the temporal coherence of videos and multi-modality in terms of diversity …
Order matters: Shuffling sequence generation for video prediction
Predicting future frames in natural video sequences is a new challenge that is receiving
increasing attention in the computer vision community. However, existing models suffer from …
increasing attention in the computer vision community. However, existing models suffer from …
Intermittent deployment for large-scale multi-robot forage perception: Data synthesis, prediction, and planning
Monitoring the health and vigor of grasslands is vital for informing management decisions to
optimize rotational grazing in agriculture applications. To take advantage of forage …
optimize rotational grazing in agriculture applications. To take advantage of forage …
[HTML][HTML] Learning sparse and meaningful representations through embodiment
How do humans acquire a meaningful understanding of the world with little to no
supervision or semantic labels provided by the environment? Here we investigate …
supervision or semantic labels provided by the environment? Here we investigate …
TAFormer: A Unified Target-Aware Transformer for Video and Motion Joint Prediction in Aerial Scenes
L Xu, W Lu, H Yu, Y Mao, H Bi, C Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As drone technology advances, using unmanned aerial vehicles for aerial surveys has
become the dominant trend in modern low-altitude remote sensing. The surge in aerial …
become the dominant trend in modern low-altitude remote sensing. The surge in aerial …
Pair-wise layer attention with spatial masking for video prediction
P Li, C Zhang, Z Yang, X Xu, M Song - arXiv preprint arXiv:2311.11289, 2023 - arxiv.org
Video prediction yields future frames by employing the historical frames and has exhibited
its great potential in many applications, eg, meteorological prediction, and autonomous …
its great potential in many applications, eg, meteorological prediction, and autonomous …