MemoryMamba: Memory-Augmented State Space Model for Defect Recognition

arXiv:2405.03673v1 Announce Type: new
Abstract: As automation advances in manufacturing, the demand for precise and sophisticated defect detection technologies grows. Existing vision models for defect recognition methods are insufficient for handling the complexities and variations of defects in contemporary manufacturing settings. These models especially struggle in scenarios involving limited or imbalanced defect data. In this work, we introduce MemoryMamba, a novel memory-augmented state space model (SSM), designed to overcome the limitations of existing defect recognition models. MemoryMamba integrates the state …

abstract advances arxiv automation complexities cs.ai cs.cv defect detection defects demand detection manufacturing memory recognition space state state space model struggle technologies type vision vision models