Mar 22, 2023 · In this work, we develop a learning system based on convolutional neural network (CNN) to implement the incremental learning mode for image classification ...
And a mechanism composed of knowledge distillation and fine-tuning is also included to consolidate the learned knowledge using associations with the new task.
Mar 22, 2023 · In this work, we develop a learning system based on convolutional neural network (CNN) to implement the incremental learning mode for image.
Mar 22, 2023 · Incremental learning without looking back: a neural connection relocation approach. March 2023; Neural Computing and Applications 35(19):1-15.
And a mechanism composed of knowledge distillation and fine-tuning is also included to consolidate the learned knowledge using associations with the new task.
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This work proposes the Learning without Forgetting method, which uses only new task data to train the network while preserving the original capabilities.
Jul 29, 2019 · Learning without Forgetting (LwF) is an incremental learning (sometimes also called continual or lifelong learning) technique for neural networks.
Missing: relocation | Show results with:relocation
Aug 12, 2020 · I build the incremental learning model it must never forget what it has learned. That is when it learns something new it can't forget something it already ...
Missing: relocation | Show results with:relocation
Mar 22, 2021 · In this paper, we shed light on an on-call transfer set to provide past experiences whenever a new class arises in the data stream.
Missing: relocation approach.
Dec 5, 2022 · Main. An important open problem in deep learning is enabling neural networks to incrementally learn from non-stationary streams of data.
Missing: relocation | Show results with:relocation