MRI to digital medicine diagnosis: integrating deep learning into clinical decision-making for lumbar degenerative diseases [PDF]
Frontiers in SurgeryIntroductionTo develop an intelligent system based on artificial intelligence (AI) deep learning algorithms using deep learning tools, aiming to assist in the diagnosis of lumbar degenerative diseases by identifying lumbar spine magnetic resonance images
Baoyi Ke +8 more
doaj +2 more sources
Multi-Scale Vehicle Detection for Foreground-Background Class Imbalance with Improved YOLOv2
Sensors, 2019 Vehicle detection is a challenging task in computer vision. In recent years, numerous vehicle detection methods have been proposed. Since the vehicles may have varying sizes in a scene, while the vehicles and the background in a scene may be with ...
Hong Xiang +2 more
exaly +3 more sources
Vehicle Detection on Occupancy Grid Maps: Comparison of Five Detectors Regarding Real-Time Performance [PDF]
Sensors, 2023 Occupancy grid maps are widely used as an environment model that allows the fusion of different range sensor technologies in real-time for robotics applications.
Nils Defauw +4 more
doaj +2 more sources
A multi-robot collaborative manipulation framework for dynamic and obstacle-dense environments: integration of deep learning for real-time task execution [PDF]
Frontiers in Robotics and AIThis paper presents a multi-robot collaborative manipulation framework, implemented in the Gazebo simulation environment, designed to enable the execution of autonomous tasks by mobile manipulators in dynamic environments and dense obstacles.
Afnan Ahmed Adil +3 more
doaj +2 more sources
A Novel Approach to Detect Drones Using Deep Convolutional Neural Network Architecture [PDF]
SensorsOver the past decades, drones have become more attainable by the public due to their widespread availability at affordable prices. Nevertheless, this situation sparks serious concerns in both the cyber and physical security domains, as drones can be ...
Hrishi Rakshit, Pooneh Bagheri Zadeh
doaj +2 more sources
A Real-Time Chinese Traffic Sign Detection Algorithm Based on Modified YOLOv2
Algorithms, 2017 Traffic sign detection is an important task in traffic sign recognition systems. Chinese traffic signs have their unique features compared with traffic signs of other countries.
Jianming Zhang +2 more
exaly +3 more sources
Multi-Object Detection using Enhanced YOLOv2 and LuNet Algorithms in Surveillance Videos
E-PrimeMultiple object tracking (MOT) in videos benefits multiple applications, including robot navigation, video surveillance, video analytics, and intelligent transportation systems.
T. Mohandoss, J. Rangaraj
exaly +3 more sources
Maximizing YOLOv2 efficiency: A study on multiclass detection of indoor objects
Results in EngineeringThe objective of the present study is to present a systematic approach for optimizing the key hyperparameters of YOLOv2 model for multiclass object detection, specifically targeting seven classes of indoor objects: chair, fire extinguisher, printer ...
G Divya Deepak, Subraya Krishna Bhat
exaly +3 more sources
Motorcycle detection based on deep learning implemented on FPGA [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2021 This paper proposes a hardware accelerator design for motorcycle detection based on deep learning. We designed the training parameters by K-means algorithm and created the motorcycle dataset from Thailand's urban scene.
Feng Peng +3 more
doaj +1 more source
RFID tag group recognition based on motion blur estimation and YOLOv2 improved by Gaussian [PDF]
Metrology and Measurement Systems, 2022 Effective recognition of tags in the dynamic measurement system would significantly improve the reading performance of the tag group, but the blurred outline and appearance of tag images captured in motion seriously limit the effectiveness of the ...
Lin Li +5 more
doaj +1 more source