Understanding deep learning techniques for image segmentation
The machine learning community has been overwhelmed by a plethora of deep learning--
based approaches. Many challenging computer vision tasks, such as detection, localization …
based approaches. Many challenging computer vision tasks, such as detection, localization …
Human movement datasets: An interdisciplinary scoping review
Movement dataset reviews exist but are limited in coverage, both in terms of size and
research discipline. While topic-specific reviews clearly have their merit, it is critical to have a …
research discipline. While topic-specific reviews clearly have their merit, it is critical to have a …
A survey of content-aware video analysis for sports
HC Shih - IEEE Transactions on circuits and systems for video …, 2017 - ieeexplore.ieee.org
Sports data analysis is becoming increasingly large scale, diversified, and shared, but
difficulty persists in rapidly accessing the most crucial information. Previous surveys have …
difficulty persists in rapidly accessing the most crucial information. Previous surveys have …
A mixed-perception approach for safe human–robot collaboration in industrial automation
Digital-enabled manufacturing systems require a high level of automation for fast and low-
cost production but should also present flexibility and adaptiveness to varying and dynamic …
cost production but should also present flexibility and adaptiveness to varying and dynamic …
[PDF][PDF] An optimized architecture of image classification using convolutional neural network
The convolutional neural network (CNN) is the type of deep neural networks which has been
widely used in visual recognition. Over the years, CNN has gained lots of attention due to its …
widely used in visual recognition. Over the years, CNN has gained lots of attention due to its …
3D-GIoU: 3D generalized intersection over union for object detection in point cloud
J Xu, Y Ma, S He, J Zhu - Sensors, 2019 - mdpi.com
Three-dimensional (3D) object detection is an important research in 3D computer vision with
significant applications in many fields, such as automatic driving, robotics, and human …
significant applications in many fields, such as automatic driving, robotics, and human …
Action recognition based on two-stream convolutional networks with long-short-term spatiotemporal features
Y Wan, Z Yu, Y Wang, X Li - IEEE Access, 2020 - ieeexplore.ieee.org
Human action recognition is an important research topic in the field of computer vision due
to its application values. Recently, a variety of approaches based on deep learning features …
to its application values. Recently, a variety of approaches based on deep learning features …
Human action recognition systems: A review of the trends and state-of-the-art
Human action recognition (HAR), deeply rooted in computer vision, video surveillance,
automated observation, and human-computer interaction (HCI), enables precise …
automated observation, and human-computer interaction (HCI), enables precise …
Human action interpretation using convolutional neural network: a survey
Z Malik, MIB Shapiai - Machine Vision and Applications, 2022 - Springer
Human action interpretation (HAI) is one of the trending domains in the era of computer
vision. It can further be divided into human action recognition (HAR) and human action …
vision. It can further be divided into human action recognition (HAR) and human action …
DTW-CNN: time series-based human interaction prediction in videos using CNN-extracted features
Recently, the prediction of interactions in videos has been an active subject in computer
vision. Its goal is to deduce interactions in their early stages. Many approaches have been …
vision. Its goal is to deduce interactions in their early stages. Many approaches have been …