An Overview of Deep Neural Networks for Few-Shot Learning

J Zhao, L Kong, J Lv - Big Data Mining and Analytics, 2024 - ieeexplore.ieee.org
Recent advancements in deep learning have led to significant breakthroughs across various
fields. However, these methods often require extensive labeled data for optimal …

Conan: Conditional neural aggregation network for unconstrained face feature fusion

B Jawade, DD Mohan, D Fedorishin… - … Joint Conference on …, 2023 - ieeexplore.ieee.org
Face recognition from image sets acquired under unregulated and uncontrolled settings,
such as at large distances, low resolutions, varying viewpoints, illumination, pose, and …

An End-to-End Air Writing Recognition Method Based on Transformer

X Tan, J Tong, T Matsumaru, V Dutta, X He - IEEE Access, 2023 - ieeexplore.ieee.org
The air-writing recognition task entails the computer's ability to directly recognize and
interpret user input generated by finger movements in the air. This form of interaction …

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation

AM Vepa, Z Yang, A Choi, J Joo, F Scalzo… - arXiv preprint arXiv …, 2024 - arxiv.org
Deep learning has seen remarkable advancements in machine learning, yet it often
demands extensive annotated data. Tasks like 3D semantic segmentation impose a …

The Reality of Artificiality: The Impact of Artificial Intelligence on Language and Culture Course Assessments and Rubrics

T Lobalsamo, D Segreti, MJ Jamali… - AI in Language Teaching …, 2024 - igi-global.com
As artificial intelligence (AI) continues to increase its presence and accessibility within
education, the need to address AI's impact on assignment design and the production of …