0% Complete
Home
/
12th International Conference on Computer and Knowledge Engineering
A Survey on Semi-Automated and Automated Approaches for Video Annotation
Authors :
Samin Zare
1
Mehran Yazdi
2
1- Shiraz university
2- Shiraz university
Keywords :
video annotation،machine learning،data labeling،computer vision،deep learning
Abstract :
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 autonomous driving and processing huge volumes of video data. Nevertheless, labeling frame-by-frame of video datasets is extremely cost-prohibiting and time-consuming. Therefore, the development of effective annotation systems will be crucial for the generation of proper annotations for large-scale datasets of video. This survey paper briefly reviews novel representative literature and systematizes the commonalities in different machine learning techniques such as supervised learning, active learning, transfer learning, and neural networks. We consider some reviews that introduce annotation tools as well. Ultimately, we summarized the performances of all the mentioned approaches applied to various datasets and demonstrated the experimental results.
Papers List
List of archived papers
A Novel Hybrid Method for Clustering Text Documents using Evolutionary Optimization
Muhammad Naderi - Maryam Amiri
Virtual Network Embedding based on Univariate Distribution Estimation
Arezoo Jahani
Deep Learning Based High-Resolution Edge Detection for Microwave Imaging using a Variational Autoencoder
Seyed Reza Razavi Pour - Leila Ahmadi - Amir Ahmad Shishegar
Plant Disease Detection Using Dynamic Knowledge Distillation and Attention Mechanism
Mohammad Ghasemi Arian - Mohammad Hossein Yaghmaee Moghaddam
Improve the utility of tensor cores by compacting sparse matrix technique
Mohammad.S Abazari - Mahsa Zahedi - Abdorreza Savadi
A large input-space-margin approach for adversarial training
Reihaneh Nikouei - Mohammad Taheri
Robustness Scan of Digital Circuits Using Convolutional Neural Networks
Mobin Vaziri - Mohammad Mehdi Rahimifar - Hadi Jahanirad
DPRNN-FORMER: AN EFFICIENT WAY TO DEAL WITH BLIND SOURCE SEPARATION
Ramin Ghorbani - Sajad Haghzad Klidbary
Efficient Vision Transformer for Accurate Traffic Sign Detection
Javad Mirzapour Kaleybar - Hooman Khaloo - Avaz Naghipour
TD-PINNs: Efficient Shared-Memory Parallelization of Physics-Informed Neural Networks for Time-Dependent PDEs
Mahdi Movahedian Moghaddam - Kourosh Parand
more
Samin Hamayesh - Version 44.5.0