30 citations · 35 across the 4 of their papers we have counts for
4 papers · 2 filters
RILOD: Near Real-Time Incremental Learning for Object Detection at the Edge
Dawei Li, Serafettin Tasci, Shalini Ghosh +3
Object detection models shipped with camera-equipped edge devices cannot cover the objects of interest for every user. Therefore, the incremental learning capability is a critical…
Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML
Jie Zhang, Junting Zhang, Shalini Ghosh +4
Lifelong learning, the problem of continual learning where tasks arrive in sequence, has been lately attracting more attention in the computer vision community. The aim of lifelong…
Class-incremental Learning via Deep Model Consolidation
Junting Zhang, Jie Zhang, Shalini Ghosh +5
Deep neural networks (DNNs) often suffer from "catastrophic forgetting" during incremental learning (IL) --- an abrupt degradation of performance on the original set of classes whe…
MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression
Jie Zhang, Xiaolong Wang, Dawei Li +3
State-of-the-art deep model compression methods exploit the low-rank approximation and sparsity pruning to remove redundant parameters from a learned hidden layer. However, they pr…