A survey on semi-automated and automated approaches for video annotation
Video analytics systems have recently gained intensive attention due to the fact that they
play a practical role in a broad range of topics, including understanding scenes in …
play a practical role in a broad range of topics, including understanding scenes in …
Predicting electricity consumption using deep recurrent neural networks
Electricity consumption has increased exponentially during the past few decades. This
increase is heavily burdening the electricity distributors. Therefore, predicting the future …
increase is heavily burdening the electricity distributors. Therefore, predicting the future …
Analysis of energy consumption using RNN-LSTM and ARIMA Model
MM Sachin, MP Baby, AS Ponraj - Journal of Physics …, 2020 - iopscience.iop.org
Given the increase of smart electricity meters and the wide adoption of electricity generation
technologies such as solar panels, there is a wealth of data available on the usage of …
technologies such as solar panels, there is a wealth of data available on the usage of …
Characterising video segments to support learning
A Mohammed, V Dimitrova - ICCE 2020 Proceedings, 2020 - eprints.whiterose.ac.uk
Videos provide opportunities for engagement and independent learning and are widely
used in various learning contexts. However, there are challenges with using videos for …
used in various learning contexts. However, there are challenges with using videos for …
Video Annotator: A framework for efficiently building video classifiers using vision-language models and active learning
A Ziai, A Vartakavi - arXiv preprint arXiv:2402.06560, 2024 - arxiv.org
High-quality and consistent annotations are fundamental to the successful development of
robust machine learning models. Traditional data annotation methods are resource …
robust machine learning models. Traditional data annotation methods are resource …
Detecting objects and people and tracking movements in a video using tensorflow and deeplearning
J Bornia, A Frihida, C Claramunt - 2020 4th International …, 2020 - ieeexplore.ieee.org
With the advent of the digital age and more specifically videos, a huge amount of data is
produced every day such as television archiving, video surveillance, etc. Faced with the …
produced every day such as television archiving, video surveillance, etc. Faced with the …
A state-of-art review on automatic video annotation techniques
Video annotation has gained attention because of the rapid development of video
information and wide usage of video analysis in all directions. With the capacity of depicting …
information and wide usage of video analysis in all directions. With the capacity of depicting …
No-code MLOps Platform for Data Annotation
H Kim, B Kim, W Lu, L Li - 2023 IEEE International Conference …, 2023 - ieeexplore.ieee.org
The increasing demand for large-scale training data in deep learning models has
underscored the significance of efficient data annotation. However, manual labeling remains …
underscored the significance of efficient data annotation. However, manual labeling remains …
Towards a semantic video analysis using deep learning and ontology
J Bornia, SA Mahmoudi, A Frihida… - 2018 4th International …, 2018 - ieeexplore.ieee.org
With the technological advances in the field of multimedia, associated with the
generalization of their uses in many applications such as television archiving, motion …
generalization of their uses in many applications such as television archiving, motion …
Video tagging and recommender system using deep learning
V Garg, VA Markhedkar, SS Lale… - … and Computer Vision …, 2021 - Springer
In today's digital era, video tagging has gained its importance to acknowledge the fact that
searching for appropriate videos is a waste of time. In this paper, we address the problem of …
searching for appropriate videos is a waste of time. In this paper, we address the problem of …