Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging
Autism spectrum disorder (ASD) is a neurodevelopmental incurable disorder with a long
diagnostic period encountered in the early years of life. If diagnosed early, the negative …
diagnostic period encountered in the early years of life. If diagnosed early, the negative …
Detection of epileptic seizure using pretrained deep convolutional neural network and transfer learning
Introduction: The diagnosis of epilepsy takes a certain process, depending entirely on the
attending physician. However, the human factor may cause erroneous diagnosis in the …
attending physician. However, the human factor may cause erroneous diagnosis in the …
CNN feature based graph convolutional network for weed and crop recognition in smart farming
H Jiang, C Zhang, Y Qiao, Z Zhang, W Zhang… - … and electronics in …, 2020 - Elsevier
Weeding is an effective way to increase crop yields. Reliable and accurate weed recognition
is a prerequisite for achieving high-precision site-specific weed control in precision …
is a prerequisite for achieving high-precision site-specific weed control in precision …
Crack detection using fusion features‐based broad learning system and image processing
Deep learning has been widely applied to vision‐based structural damage detection, but its
computational demand is high. To avoid this computational burden, a novel crack detection …
computational demand is high. To avoid this computational burden, a novel crack detection …
Cross‐scene pavement distress detection by a novel transfer learning framework
Deep learning has achieved promising results in pavement distress detection. However, the
training model's effectiveness varies according to the data and scenarios acquired by …
training model's effectiveness varies according to the data and scenarios acquired by …
Deep learning techniques for recommender systems based on collaborative filtering
Abstract In the Big Data Era, recommender systems perform a fundamental role in data
management and information filtering. In this context, Collaborative Filtering (CF) persists as …
management and information filtering. In this context, Collaborative Filtering (CF) persists as …
Integrating structural control, health monitoring, and energy harvesting for smart cities
S Javadinasab Hormozabad, M Gutierrez Soto… - Expert …, 2021 - Wiley Online Library
Cities that are adopting innovative and technology‐driven solutions to improve the city's
efficiency are considered smart cities. With the increased attention on smart cities with self …
efficiency are considered smart cities. With the increased attention on smart cities with self …
Gcnnmatch: Graph convolutional neural networks for multi-object tracking via sinkhorn normalization
This paper proposes a novel method for online Multi-Object Tracking (MOT) using Graph
Convolutional Neural Network (GCNN) based feature extraction and end-to-end feature …
Convolutional Neural Network (GCNN) based feature extraction and end-to-end feature …
Machine learning and image processing approaches for estimating concrete surface roughness using basic cameras
A Valikhani, A Jaberi Jahromi… - … ‐Aided Civil and …, 2021 - Wiley Online Library
Casting concrete at different ages for new construction and repairing or retrofitting concrete
structures requires a sufficient bond between concrete casts. The bond strength between …
structures requires a sufficient bond between concrete casts. The bond strength between …
Deep learning‐based object identification with instance segmentation and pseudo‐LiDAR point cloud for work zone safety
J Shen, W Yan, P Li, X Xiong - Computer‐Aided Civil and …, 2021 - Wiley Online Library
Automated object identification in three‐dimensional (3D) space is crucial for work zone
safety, such as compliance with construction rules and preventing workplace injuries and …
safety, such as compliance with construction rules and preventing workplace injuries and …