IEEE

Unsupervised Representation Learning and Explainable Clustering for Wafer Map Pattern Analysis

Abstract: As wafer maps become increasingly complex and high-dimensional, conventional clustering methods often fail to uncover subtle but meaningful defect patterns critical for yield enhancement and ...
Frontiers

Latent Profiling of Five-Dimensional Psychological Resilience Across Generations: A Deep Clustering and Behavioral Divergence Analysis in Pre-Conflict Iran

The final, formatted version of the article will be published soon. Psychological resilience is increasingly conceptualized as a multidimensional construct encompassing identity, emotional, cognitive, ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
IEEE

TCL: Time-Dependent Clustering Loss for Optimizing Post-Training Feature Map Quantization for Partitioned DNNs

Abstract: This paper introduces an enhanced approach for deploying deep learning models on resource-constrained IoT devices by combining model partitioning, autoencoder-based compression, quantization ...