… This paper provides a comprehensive survey on FSCIL. Unlike previous surveys, we aim
to synthesize few-shot learning and incremental learning, focusing on introducing FSCIL from …

… Given this lack of coherent terminology in the literature, for the purpose of this survey we
define incremental learning as continual learning systems that learn from a sequence of tasks …

… -incremental learning, an algorithm must incrementally learn … ) in domain-incremental learning,
an algorithm must learn the … -incremental learning, an algorithm must incrementally learn …

… 2, we start with definitions and concepts related to the incremental learning. The principal …
on the old and the new training data. The incremental learning is a type of training; we can say …

… In class incremental learning, old class samples are generally not available while training
on new class samples. Although keeping a portion of old class samples in a memory buffer …

… In our task/difficulty incremental learning setting, we have implemented LwF to retain the
old knowledge learnt from previous encountering segment data with different environmental …

… Originality of this work includes the consideration of an incremental learning stage …
computing methods: A case study of micromilling processes,” IEEE Trans. Ind. Informat., vol. …

… This paper designs and evaluates incremental learning solutions for real-world fraud … shows
that incremental learning is a competitive alternative to conventional batch learning settings …

… Towards that purpose, we put forward a Graph Pseudo Incremental Learning paradigm by
… arbitrary number of training episodes for our model to practice the incremental learning skill. …

… Once the feature extraction is complete, we can move onto training the incremental learning
model that will ultimately be used to identify defects from welding signal data. In this work, a …