A deep learning-based hybrid framework for object detection and recognition in autonomous driving
As a key technology of intelligent transportation system, the intelligent vehicle is the carrier
of comprehensive integration of many technologies. Although vision-based autonomous …
of comprehensive integration of many technologies. Although vision-based autonomous …
LaneScanNET: A deep-learning approach for simultaneous detection of obstacle-lane states for autonomous driving systems
Autonomous driving is the future of the automotive industry across the globe. Many
challenges must be resolved in designing and developing successful Autonomous Driving …
challenges must be resolved in designing and developing successful Autonomous Driving …
Object detection and depth estimation approach based on deep convolutional neural networks
In this paper, we present a real-time object detection and depth estimation approach based
on deep convolutional neural networks (CNNs). We improve object detection through the …
on deep convolutional neural networks (CNNs). We improve object detection through the …
Pothole Detection Using YOLOv3 Model
When it comes to moving people and goods around a country, road transports are like the
heart and arteries. It is essential that roads need be kept in good shape at all times. Most of …
heart and arteries. It is essential that roads need be kept in good shape at all times. Most of …
Advanced Night time Object Detection in Driver-Assistance Systems using Thermal Vision and YOLOv5
HT Vo, LD Quach - International Journal of Advanced …, 2023 - search.proquest.com
Driver-assistance systems have become an indispensable component of modern vehicles,
serving as a crucial element in enhancing safety for both drivers and passengers. Among …
serving as a crucial element in enhancing safety for both drivers and passengers. Among …
Sensor fusion of camera and LiDAR raw data for vehicle detection
G Danapal, GA Santos, JPCL da Costa… - 2020 Workshop on …, 2020 - ieeexplore.ieee.org
Autonomous vehicles are expected to save almost half-million lives between 2035 to 2045.
Moreover, since 90% of the accidents are caused by humans, 9% by weather and road …
Moreover, since 90% of the accidents are caused by humans, 9% by weather and road …
Road object detection in Bangladesh using Faster R-CNN: a deep learning approach
The importance of object detection in our lives is increasing day by day. The role of object
detection is very important in autonomous cars, intelligent driving assistance, and advanced …
detection is very important in autonomous cars, intelligent driving assistance, and advanced …
Robust approach to supervised deep neural network training for real-time object classification in cluttered indoor environment
B Endale, A Tullu, H Shi, BS Kang - Applied Sciences, 2021 - mdpi.com
Unmanned aerial vehicles (UAVs) are being widely utilized for various missions: in both
civilian and military sectors. Many of these missions demand UAVs to acquire artificial …
civilian and military sectors. Many of these missions demand UAVs to acquire artificial …
Deep Learning-Based Object Detection Techniques for Self-Driving Cars: an in-Depth Analysis
B Isong, T Mashego, J Moemi… - … Conference on Electrical …, 2023 - ieeexplore.ieee.org
Self-driving cars are poised to transform transportation, but ensuring safe and reliable
autonomous driving via robust object detection remains a critical challenge. This review …
autonomous driving via robust object detection remains a critical challenge. This review …
A Systematic Literature Review: Object Detection in Semi-Autonomous Car
E Sunjaya, C Daniel, A Kurniawan… - … of Computer and …, 2023 - ieeexplore.ieee.org
Traffic accidents are a serious problem in developing countries. These accidents can be
caused by poor infrastructure and the arrogance of drivers. In addition, semi-autonomous …
caused by poor infrastructure and the arrogance of drivers. In addition, semi-autonomous …