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Status: Unchecked ×Keyword: convolutional filters ×Clear all

1 claim from 1 paper

1. Computer Science › Advanced Neural Network Applications

   Kernel clustering-based deep model pruning for few category datasets

   Huang, Xie, Wang and Wu · Intelligent Data Analysis · 2025

   The paper proposes Cluster-based Redundancy Elimination (CRE), which prunes redundant convolutional filters in deep models for datasets with few categories, without finetuning, and reports it beating other pruning methods.

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   1. UncheckedThe authors say their pruning method removes the need for finetuning, so deep models keep their ability to generalise.“This approach eliminates the need for finetuning, thus preserving the generalization of deep models.”