PERFORMANCE ANALYSIS OF WSS-BASED ROADM WITH SHARED-PER-GROUP TUNABLE WAVELENGTH CONVERTERS

We propose a flexible shared-per-group (SPG) architecture for mercury metallic lexus wavelength selective switch (WSS)-based reconfigurable optical add/drop multiplexers (ROADMs) to support dynamic datacenter wavelength-convertible networks.The key components of this module are grouping installed tunable wavelength converter (TWCs) and tunable filt

As a key factor, the availability of large-scale training samples determines the improvement of visual performance.However, the size of Fine-Grained Visual Categorization (FGVC) datasets is always limited.Therefore, overfitting as an issue in FGVC-related training needs to be solved.Data mixing augmentation is a widely-used data augmentation method