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Abstract: In this paper, we design an ambient vehicle path prediction model based on deep learning. The most important goal of the autonomous driving system ...
Proposed sequential rasterized-image based trajectory prediction model. ... safer predictions will be possible if these deep learning models and trajectory ...
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Objectives: Accurately predicting when patients with mild cognitive impairment (MCI) will progress to dementia is a formidable challenge.
The proposed model can predict the vehicle's future path in freeway by observing the images related to the history of the target vehicle's movement and its ...
Missing: Rasterized | Show results with:Rasterized
Jul 12, 2023 · 1) Physics-based Models: These methods rely on the laws of physics and kinematics principles to predict the future trajectory of a vehicle. They ...
Nov 14, 2023 · The GAN model comprises two networks: generators and discriminators. The generator generates multiple possible paths, and the discriminator ...
Missing: Rasterized | Show results with:Rasterized
Nov 19, 2023 · Based on existing state-of-the-art research, the multi-path of multi-agents was predicted using a generative model, and the actor's trajectory ...
Road-Aware Trajectory Prediction for Autonomous Driving on Highways
www.ncbi.nlm.nih.gov › PMC7506803
Aug 20, 2020 · We developed a data-efficient learning framework for the trajectory prediction network in the curvilinear coordinate system of the road and a ...
May 30, 2022 · rasterized [21] RGB image M to the model. 5.2.2 Model Output. Given the past motion sequence ST = [S1. T , ..., S tpred. T. ] and the context ...
This is a checklist of state-of-the-art research materials (datasets, blogs, papers and public codes) related to trajectory prediction.