http://bing.comIJCAI 2022 IFS-SED: Incremental Few-Shot Sound Event Detection Using Explicit Learning and Calibration字幕版之后会放出,敬请持续关注欢迎加入人工智能机器学习群:556910946,公众号: AI基地,会有视频,资料放送。公众号中输入视频地址或视频ID就可
SALNet: Semi-Supervised Few-Shot Text Classification with Attention-Based Lexicon Construction Few-Shot Learning for Multi-Label Intent Detection Few-Shot Class-Incremental Learning via Relation Knowledge Distillation A Bidirectional Multi-Paragraph Reading Model for Zero-Shot Entity Linking Leveraging Table ...
SemSup-XC: Semantic supervision for zero and few-shot extreme classification Zero- and few-shot event detection via prompt-based meta learning HINT: Hypernetwork instruction tuning for efficient zero- and few-shot generalisation What does the failure to reason with "respectively" in zero/few-shot ...
With emerging online topics as a source for numerous new events, detecting unseen / rare event types presents an elusive challenge for existing event detection methods, where only limited data access is provided for training. To address the data scarcity problem in event detection, we propose Meta...
We address the problem of anomaly detection in videos. The goal is to identify unusual behaviours automatically by learning exclusively from normal videos. Most existing approaches are usually data-hungry and have limited generalization abilities. They u
In this paper, we propose a new continual learning framework for few-shot bioacoustic event detection (BED). First, we modify the recently proposed dynamic... X Wu,D Xu,H Wei,... 被引量: 0发表: 2023年 Few-shot incremental learning with continual prototype calibration for remote sensing ...
The feature extractor module is implemented using a 20-layer ResNet, and the few-shot class incremental learning (FSCIL) is carried out via a constantly updated classifier (CUC), which is further enhanced by incorporating an attention mechanism for measuring the prototype similarity between each ...
An Incremental Class-Learning Approach with Acoustic Novelty Detection for Acoustic Event Recognition. Sensors 2021, 21, 6622. [Google Scholar] [CrossRef] Snell, J.; Swersky, K.; Zemel, R.S. Prototypical networks for few-shot learning. arXiv 2017, arXiv:1703.05175. [Google Scholar] Fink, ...
[44] proposed a new meta-learning-based incremental few-shot object detection method, which took CenterNet as its fundamental framework and redesigned it by introducing a novel meta-learning method, thereby adapting the model to unseen knowledge while overcoming the problem of forgetting to a great...
The emergence of few-shot object detection provides a new approach to address the challenge of poor generalization ability due to data scarcity. Currently, extensive research has been conducted on few-shot object detection in natural scene datasets, and notable progress has been made. However, in ...