WebJul 14, 2024 · In this paper, we present a novel incremental learning technique to solve the catastrophic forgetting problem observed in the CNN architectures. We used a progressive deep neural network to incrementally learn new classes while keeping the performance of the network unchanged on old classes. The incremental training requires us to train the … WebFeb 23, 2024 · PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three …
Meta-Aggregation Networks for Class-Incremental Learning
WebNov 3, 2024 · A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks. Eden Belouadah, Adrian Popescu, Ioannis Kanellos. The ability of artificial agents … WebApr 2, 2024 · Class-Incremental Learning by Knowledge Distillation with Adaptive Feature Consolidation Minsoo Kang, Jaeyoo Park, Bohyung Han We present a novel class incremental learning approach based on deep neural networks, which continually learns new tasks with limited memory for storing examples in the previous tasks. raleigh ccm bop
Class Incremental Learning Papers With Code
WebApr 4, 2024 · The proposed approach has a unique perspective to utilize the previous knowledge in class incremental learning since it augments features of arbitrary target classes using examples in other classes via adversarial attacks on a previously learned classifier. By allowing the cross-class feature augmentations, each class in the old tasks ... WebJun 9, 2024 · To build a model that can learn novel classes while maintaining discrimination ability for old categories. We will be implementing the Maintaining Discrimination and … raleigh cbs tv