2025-08-29 · 1 min read
The project adopted a wireless device and established a fabric images dataset with elaborated structure parameters. Presented a multi-task and multi-scale convolutional neural network (MTMSnet) to recognize the fabric density, weaving pattern, reaching under 2% and 10% error respectively.
2025-08-29 · 3 min read
Is it possible to integrate these complex tools into a single, intelligent entry point, allowing researchers to complete the entire process from image analysis to performance prediction using only the most natural form of interaction—language conversation?
2025-08-28 · 2 min read
This project designed and implemented the SAM-Fiber (Segment Anything Model for Fiber) framework. Instead of simply applying a general-purpose model, it transforms the powerful vision foundation model (SAM2) into a specialized fiber analysis tool through a series of innovations.
2025-08-28 · 3 min read
The core of this project is an end-to-end intelligent system composed of two parts: a YOLO-OCR model for automatically extracting scale information, and an interactive measurement front-end powered by MicroSAM that integrates this information.
2025-08-28 · 3 min read
The framework's core leverages the domain-specific large language model SciBERT, trained on a newly developed, specialized electrospinning corpus to achieve high-precision Named Entity Recognition (NER) and Relation Extraction (RE).