Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …
detect driver inattention is essential in building a safe yet intelligent transportation system …
Computer vision‐based recognition of driver distraction: A review
Vehicle crash rates caused by distracted driving have been rising in recent years. Hence,
safety while driving on roads is today a crucial concern across the world. Some of the …
safety while driving on roads is today a crucial concern across the world. Some of the …
An end to end deep neural network for iris segmentation in unconstrained scenarios
With the increasing imaging and processing capabilities of today's mobile devices, user
authentication using iris biometrics has become feasible. However, as the acquisition …
authentication using iris biometrics has become feasible. However, as the acquisition …
Predicting concentration levels of air pollutants by transfer learning and recurrent neural network
Air pollution (AP) poses a great threat to human health, and people are paying more
attention than ever to its prediction. Accurate prediction of AP helps people to plan for their …
attention than ever to its prediction. Accurate prediction of AP helps people to plan for their …
Convolutional neural network implementation for eye-gaze estimation on low-quality consumer imaging systems
J Lemley, A Kar, A Drimbarean… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Accurate and efficient eye gaze estimation is important for emerging consumer electronic
systems, such as driver monitoring systems and novel user interfaces. Such systems are …
systems, such as driver monitoring systems and novel user interfaces. Such systems are …
Real-time driver state monitoring using a CNN based spatio-temporal approach
Many road accidents occur due to distracted drivers. Today, driver monitoring is essential
even for the latest autonomous vehicles to alert distracted drivers in order to take over …
even for the latest autonomous vehicles to alert distracted drivers in order to take over …
Driver distraction recognition using 3d convolutional neural networks
The number of road accidents and deaths due to distracted driving is continuously
increasing in recent years. Usage of mobile phones, talking to passengers and reaching …
increasing in recent years. Usage of mobile phones, talking to passengers and reaching …
Convolutional neural network model for variety classification and seed quality assessment of winter rapeseed
P Rybacki, J Niemann, K Bahcevandziev, K Durczak - Sensors, 2023 - mdpi.com
The main objective of this study is to develop an automatic classification model for winter
rapeseed varieties, to assess seed maturity and damage based on seed colour using a …
rapeseed varieties, to assess seed maturity and damage based on seed colour using a …
Deep learning algorithm to detect cardiac sarcoidosis from echocardiographic movies
S Katsushika, S Kodera, M Nakamoto… - Circulation …, 2021 - jstage.jst.go.jp
Background: Because the early diagnosis of subclinical cardiac sarcoidosis (CS) remains
difficult, we developed a deep learning algorithm to distinguish CS patients from healthy …
difficult, we developed a deep learning algorithm to distinguish CS patients from healthy …
Framework for user behavioural biometric identification using a multimodal scheme with keystroke trajectory feature and recurrent neural network on a mobile platform
Diverse applications are used on mobile devices. Because of the increasing dependence on
information systems, immense amounts of personal and sensitive data are stored on mobile …
information systems, immense amounts of personal and sensitive data are stored on mobile …