Deep feature annotation by iterative meta-pseudo-labeling on 2D projections
The absence of large annotated datasets to train deep neural networks (DNNs) is an issue
since manual annotation is time-consuming, expensive, and error-prone. Semi-supervised …
since manual annotation is time-consuming, expensive, and error-prone. Semi-supervised …
Data Collection and Labeling Techniques for Machine Learning
Q Huang, T Zhao - arxiv preprint arxiv:2407.12793, 2024 - arxiv.org
Data collection and labeling are critical bottlenecks in the deployment of machine learning
applications. With the increasing complexity and diversity of applications, the need for …
applications. With the increasing complexity and diversity of applications, the need for …
LabelScr: Automated Image Annotation on Mobile and Web Applications for Object Detection and Localization Model Pipelines
C Jha, G Shrivastava - 2022 IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Object localization and detection, as an emerging and demanding subject in the computer
vision community, is critical for creating next-generation computer vision systems, and over …
vision community, is critical for creating next-generation computer vision systems, and over …
Image processing based on hybrid semi-supervised learning
V Sineglazov, K Lesohorskyi… - … , Industry, and High …, 2024 - spiedigitallibrary.org
This work is devoted to the development of a new image classification method based on the
application of a hybrid semi-supervised learning algorithm for convolutional neural …
application of a hybrid semi-supervised learning algorithm for convolutional neural …
Data programming approach for weakly supervised learning of visual relations
C Gürsoy - 2024 - open.metu.edu.tr
Classifying interactions between objects in images plays an important role in extracting
meaningful information from visuals. The learning process of visual relationship …
meaningful information from visuals. The learning process of visual relationship …