Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects
Crowd behaviour analysis is an emerging research area. Due to its novelty, a proper
taxonomy to organise its different sub-tasks is still missing. This paper proposes a taxonomic …
taxonomy to organise its different sub-tasks is still missing. This paper proposes a taxonomic …
Face mask detection in COVID-19: a strategic review
With the outbreak of the Coronavirus Disease in 2019, life seemed to be had come to a
standstill. To combat the transmission of the virus, World Health Organization (WHO) …
standstill. To combat the transmission of the virus, World Health Organization (WHO) …
Moving deep learning to the edge
Deep learning is now present in a wide range of services and applications, replacing and
complementing other machine learning algorithms. Performing training and inference of …
complementing other machine learning algorithms. Performing training and inference of …
Model-driven cluster resource management for ai workloads in edge clouds
Since emerging edge applications such as Internet of Things (IoT) analytics and augmented
reality have tight latency constraints, hardware AI accelerators have been recently proposed …
reality have tight latency constraints, hardware AI accelerators have been recently proposed …
Applications of object detection in modular construction based on a comparative evaluation of deep learning algorithms
Purpose The practice of artificial intelligence (AI) is increasingly being promoted by
technology developers. However, its adoption rate is still reported as low in the construction …
technology developers. However, its adoption rate is still reported as low in the construction …
Convolutional neural network based desktop applications to classify dermatological diseases
E Göçeri - 2020 IEEE 4th international conference on image …, 2020 - ieeexplore.ieee.org
Convolutional Neural Networks (CNNs) have the potential to assist medical doctors in
diagnosis and treatment stage. This paper has been prepared to help dermatologists by …
diagnosis and treatment stage. This paper has been prepared to help dermatologists by …
Recent advances in video analytics for rail network surveillance for security, trespass and suicide prevention—A survey
T Zhang, W Aftab, L Mihaylova, C Langran-Wheeler… - Sensors, 2022 - mdpi.com
Railway networks systems are by design open and accessible to people, but this presents
challenges in the prevention of events such as terrorism, trespass, and suicide fatalities …
challenges in the prevention of events such as terrorism, trespass, and suicide fatalities …
Efficient feature-aware hybrid model of deep learning architectures for speech emotion recognition
M Ezz-Eldin, AAM Khalaf, HFA Hamed… - IEEE Access, 2021 - ieeexplore.ieee.org
Robust automatic speech emotional-speech recognition architectures based on hybrid
convolutional neural networks (CNN) and feedforward deep neural networks are proposed …
convolutional neural networks (CNN) and feedforward deep neural networks are proposed …
A continuous convolutional trainable filter for modelling unstructured data
Abstract Convolutional Neural Network (CNN) is one of the most important architectures in
deep learning. The fundamental building block of a CNN is a trainable filter, represented as …
deep learning. The fundamental building block of a CNN is a trainable filter, represented as …
Machine learning-based diffractive image analysis with subwavelength resolution
Far-field analysis of small objects is severely constrained by the diffraction limit. Existing
tools achieving subdiffraction resolution often utilize point-by-point image reconstruction via …
tools achieving subdiffraction resolution often utilize point-by-point image reconstruction via …