[HTML][HTML] The YOLO framework: A comprehensive review of evolution, applications, and benchmarks in object detection

ML Ali, Z Zhang - Computers, 2024 - mdpi.com
This paper provides a comprehensive review of the YOLO (You Only Look Once) framework
up to its latest version, YOLO 11. As a state-of-the-art model for object detection, YOLO has …

Deep directly-trained spiking neural networks for object detection

Q Su, Y Chou, Y Hu, J Li, S Mei… - Proceedings of the …, 2023 - openaccess.thecvf.com
Spiking neural networks (SNNs) are brain-inspired energy-efficient models that encode
information in spatiotemporal dynamics. Recently, deep SNNs trained directly have shown …

YOLO and Faster R-CNN object detection for smart Industry 4.0 and Industry 5.0: applications, challenges, and opportunities

N Rane - Available at SSRN 4624206, 2023 - papers.ssrn.com
The rise of Industry 4.0 and the emerging paradigm of Industry 5.0 have driven
unprecedented technological progress in various fields. Central to this transformation are …

Roadmap for cybersecurity in autonomous vehicles

VK Kukkala, SV Thiruloga… - IEEE Consumer …, 2022 - ieeexplore.ieee.org
Autonomous vehicles are on the horizon and will be transforming transportation safety and
comfort. These vehicles will be connected to various external systems and utilize advanced …

[HTML][HTML] Comparative analysis of multiple YOLO-based target detectors and trackers for ADAS in edge devices

P Azevedo, V Santos - Robotics and Autonomous Systems, 2024 - Elsevier
Accurate detection and tracking of vulnerable road users and traffic objects represent vital
tasks for autonomous driving and driving assistance systems. The recent developments in …

Enhancing autonomous driving safety: a robust traffic sign detection and recognition model TSD-YOLO

R Zhao, SH Tang, J Shen, EEB Supeni, SA Rahim - Signal Processing, 2024 - Elsevier
As autonomous driving technology rapidly advances, Traffic Sign Detection and Recognition
(TSDR) has become pivotal in ensuring the safety and regulatory compliance of …

Hyp-ow: Exploiting hierarchical structure learning with hyperbolic distance enhances open world object detection

T Doan, X Li, S Behpour, W He, L Gou… - Proceedings of the AAAI …, 2024 - ojs.aaai.org
Open World Object Detection (OWOD) is a challenging and realistic task that extends
beyond the scope of standard Object Detection task. It involves detecting both known and …

A survey of FPGA-based vision systems for autonomous cars

D Castells-Rufas, V Ngo, J Borrego-Carazo… - IEEE …, 2022 - ieeexplore.ieee.org
On the road to making self-driving cars a reality, academic and industrial researchers are
working hard to continue to increase safety while meeting technical and regulatory …

Recent Advances in 3D Object Detection for Self-Driving Vehicles: A Survey.

OA Fawole, DB Rawat - AI, 2024 - search.ebscohost.com
The development of self-driving or autonomous vehicles has led to significant
advancements in 3D object detection technologies, which are critical for the safety and …

[HTML][HTML] Few-shot object detection in remote sensing imagery via fuse context dependencies and global features

B Wang, G Ma, H Sui, Y Zhang, H Zhang, Y Zhou - Remote Sensing, 2023 - mdpi.com
The rapid development of Earth observation technology has promoted the continuous
accumulation of images in the field of remote sensing. However, a large number of remote …