Applications of convolutional neural networks in education: A systematic literature review
Applying artificial intelligence in education is relevant to addressing the current educational
crises. Many available solutions apply Convolutional Neural Networks (CNNs) to help …
crises. Many available solutions apply Convolutional Neural Networks (CNNs) to help …
IMU and smartphone camera fusion for knee adduction and knee flexion moment estimation during walking
Wearable sensing and computer vision could move biomechanics from specialized
laboratories to natural environments, but better algorithms are needed to extract meaningful …
laboratories to natural environments, but better algorithms are needed to extract meaningful …
Yolov5 enhanced learning behavior recognition and analysis in smart classroom with multiple students
Deep learning-based computer vision technology has grown stronger in recent years, and
cross-fertilization using computer vision technology has been a popular direction in recent …
cross-fertilization using computer vision technology has been a popular direction in recent …
An exptodim-macont based multiple-attribute group decision-making technique for smart classroom teaching evaluation of basic english under interval-valued …
Y Liang - IEEE Access, 2024 - ieeexplore.ieee.org
With the rapid development of information technology, the university teaching model has
also begun to break free from constraints from two dimensions of time and space, becoming …
also begun to break free from constraints from two dimensions of time and space, becoming …
[PDF][PDF] Smart classroom adoption in higher education: a thematic review
M Zairul¹, IA Ismail¹, MAM Jamil, A Azlan, IS Ismail… - 2022 - kwpublications.com
Smart classroom has become a much popular terms in 21st century education recently. The
concept of intelligence has created interest among the key players in higher education …
concept of intelligence has created interest among the key players in higher education …
ABM-SpConv-SIMD: Accelerating convolutional neural network inference for industrial IoT applications on edge devices
Convolutional Neural Networks (CNNs) have been widely deployed, while traditional cloud
data-centers based applications suffer from the bandwidth and latency network demand …
data-centers based applications suffer from the bandwidth and latency network demand …
Building robust neural networks under adversarial machine learning attacks by using biologically-inspired neurons
At the core of every artificial neural network, lie neurons which are approximate models of
their biological counterparts. However, networks that are made of artificial neurons can …
their biological counterparts. However, networks that are made of artificial neurons can …
VMLHST: Development of an Efficient Novel Virtual Reality ML Framework with Haptic Feedbacks for Improving Sports Training Scenarios
MA Tayal, M Deshmukh, V Pangave… - … Journal of Electrical …, 2023 - ijeer.forexjournal.co.in
This paper presents the development of a novel virtual reality (VR) machine learning (ML)
framework that incorporates haptic feedback to improve sports training scenarios. The …
framework that incorporates haptic feedback to improve sports training scenarios. The …
Improved YOLOv8 algorithm for classroom student behavior detection
Y Qin, Y Liao, Z Wang - 2024 IEEE 6th Advanced Information …, 2024 - ieeexplore.ieee.org
Students' classroom behavior is the main reflection of their listening status and teachers'
teaching effect. Identifying and analyzing students' behavior can obtain students' overall …
teaching effect. Identifying and analyzing students' behavior can obtain students' overall …
Learning behavior recognition in smart classroom with multiple students based on YOLOv5
Deep learning-based computer vision technology has grown stronger in recent years, and
cross-fertilization using computer vision technology has been a popular direction in recent …
cross-fertilization using computer vision technology has been a popular direction in recent …