Results 21 to 30 of about 440,724 (260)
Incremental Object Detection Inspired by Memory Mechanisms in Brain [PDF]
Jisuanji kexue, 2023 Incremental learning is key to bridging the enormous gap between artificial intelligence and human intelligence,mea-ning that agents can learn several tasks sequentially from a continuous stream of correlated data without forgetting,just as humans do ...
SHANG Di, LYU Yanfeng, QIAO Hong
doaj +1 more source
Class-Incremental Learning Based on Big Dataset Pre-Trained Models
IEEE Access, 2023 Deep neural networks have shown excellent performance in the field of pattern classification and are widely used. However, real-world data are often cannot be obtained at once, and the knowledge of old classes will be heavily forgotten when training new ...
Bin Wen, Qiuyu Zhu
doaj +1 more source
End-to-end Incremental Learning [PDF]
, 2018 Although deep learning approaches have stood out in recent years due to their state-of-the-art results, they continue to suffer from (catastrophic forgetting), a dramatic decrease in overall performance when training with new classes added incrementally.
Alahari, Karteek +4 more
core +4 more sources
Survey of Federated Incremental Learning [PDF]
Jisuanji kexueFederated learning,with its unique distributed training mode and secure aggregation mechanism,has become a research hotspot in recent years.However,in real-life scenarios,local model training often faces new data,leading to catastrophic forgetting of old
XIE Jiachen, LIU Bo, LIN Weiwei , ZHENG Jianwen
doaj +1 more source
Incremental Learning of Object Detectors without Catastrophic Forgetting [PDF]
, 2017 Despite their success for object detection, convolutional neural networks are ill-equipped for incremental learning, i.e., adapting the original model trained on a set of classes to additionally detect objects of new classes, in the absence of the ...
Alahari, Karteek +2 more
core +4 more sources
International Journal of Networked and Distributed Computing (IJNDC), 2020 This article presents the threshold-based incremental learning model for a case-base updating approach that can support adaptive detection and incremental learning of Case-based Reasoning (CBR)-based automatic adaptable phishing detection.
San Kyaw Zaw, Sangsuree Vasupongayya
doaj +1 more source
Models of incremental concept formation [PDF]
, 1988 Given a set of observations, humans acquire concepts that organize those observations and use them in classifying future experiences. This type of concept formation can occur in the absence of a tutor and it can take place despite irrelevant and ...
Fisher, Douglas +2 more
core +1 more source
Incremental learning with respect to new incoming input attributes [PDF]
, 2001 Neural networks are generally exposed to a dynamic environment where the training patterns or the input attributes (features) will likely be introduced into the current domain incrementally.
Guan, SU, Li, SC
core +2 more sources
Confidence Calibration for Incremental Learning
IEEE Access, 2020 Class incremental learning is an online learning paradigm wherein the classes to be recognized are gradually increased with limited memory, storing only a partial set of examples of past tasks.
Dongmin Kang +3 more
doaj +1 more source
Incremental multiclass open-set audio recognition
IJAIN (International Journal of Advances in Intelligent Informatics), 2022 Incremental learning aims to learn new classes if they emerge while maintaining the performance for previously known classes. It acquires useful information from incoming data to update the existing models.
Hitham Jleed, Martin Bouchard
doaj +1 more source