Výsledky vyhľadávania - "encoder–decoder Transformer"

Evaluation of Encoder-Only Transformer for Multi-Step Traffic Flow Prediction

Autori: Mas Omar Fitri Yakub Andika Aji Wijaya a ďalší

Zdroj: IEEE Access, Vol 13, Pp 106349-106368 (2025)

Predmety: encoder-only transformer, multi-step prediction, Traffic flow prediction, Electrical engineering. Electronics. Nuclear engineering, long short-term memory, encoder-decoder transformer, TK1-9971

Prístupová URL adresa: https://doaj.org/article/e76d51f8b38f42708baaec6c880e3665

MMTraP: Multi-Sensor Multi-Agent Trajectory Prediction in BEV

Autori: Sushil Sharma Arindam Das Ganesh Sistu a ďalší

Zdroj: IEEE Open Journal of Vehicular Technology, Vol 6, Pp 1551-1567 (2025)

Predmety: Transportation engineering, Sensor fusion, TA1001-1280, bird's-eye-view, semantic segmentation, multi-agent trajectory prediction, Transportation and communications, encoder-decoder transformer, HE1-9990

Prístupová URL adresa: https://doaj.org/article/fd4d59527eea4cb38ef2642b8f4f75e1

A System for Real-Time Detection of Abandoned Luggage

Autori: Ivan Vrsalovic Jonatan Lerga Marina Ivasic-Kos

Zdroj: Sensors, Vol 25, Iss 9, p 2872 (2025)

Predmety: computer vision, deep learning, object detection, YOLOv8, YOLOv11, DETR encoder–decoder transformer, Chemical technology, TP1-1185

Popis súboru: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/9/2872; https://doaj.org/toc/1424-8220

Prístupová URL adresa: https://doaj.org/article/3976e4e0e23c4df490450c7d63b716fe

BEVSeg2GTA: Joint Vehicle Segmentation and Graph Neural Networks for Ego Vehicle Trajectory Prediction in Bird’s-Eye-View

Autori: Sushil Sharma Arindam Das Ganesh Sistu a ďalší

Zdroj: IEEE Access, Vol 12, Pp 132159-132174 (2024)

Predmety: Multi-view camera, encoder-decoder transformer, Bird’s-Eye-View, semantic segmentation, graph neural network, spatio-temporal probabilistic network, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis súboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/10679361/; https://doaj.org/toc/2169-3536

Prístupová URL adresa: https://doaj.org/article/c92ba10500ec4ceaa470ecf4984aa8ce

Nemo: An Open-Source Transformer-Supercharged Benchmark for Fine-Grained Wildfire Smoke Detection

Autori: Amirhessam Yazdi Heyang Qin Connor B. Jordan a ďalší

Zdroj: Remote Sensing, Vol 14, Iss 16, p 3979 (2022)
Remote Sensing
Volume 14
Issue 16
Pages: 3979

Predmety: Science, deep learning, 02 engineering and technology, wildfire, computer vision, encoder–decoder Transformer, direct set prediction, benchmark, smoke, 13. Climate action, incipient stage, smoke density detection, 0202 electrical engineering, electronic engineering, information engineering, attention mechanism

Popis súboru: application/pdf

Prístupová URL adresa: https://doaj.org/article/8020669e221443c7b8b6213e70287a7c