[HTML][HTML] Neural architecture search: A contemporary literature review for computer vision applications
M Poyser, TP Breckon - Pattern Recognition, 2024 - Elsevier
Abstract Deep Neural Networks have received considerable attention in recent years. As the
complexity of network architecture increases in relation to the task complexity, it becomes …
complexity of network architecture increases in relation to the task complexity, it becomes …
Transductive few-shot learning with prototype-based label propagation by iterative graph refinement
Few-shot learning (FSL) is popular due to its ability to adapt to novel classes. Compared
with inductive few-shot learning, transductive models typically perform better as they …
with inductive few-shot learning, transductive models typically perform better as they …
Active learning for object detection with evidential deep learning and hierarchical uncertainty aggregation
Despite the huge success of object detection, the training process still requires an immense
amount of labeled data. Although various active learning solutions for object detection have …
amount of labeled data. Although various active learning solutions for object detection have …
Minimizing Computational Resources for Deep Machine Learning: A Compression and Neural Architecture Search Perspective for Image Classification and Object …
M POYSER - 2023 - etheses.dur.ac.uk
Computational resources represent a significant bottleneck across all current deep learning
computer vision approaches. Image and video data storage requirements for training deep …
computer vision approaches. Image and video data storage requirements for training deep …