2results about How to "Stable and smooth" patented technology

This invention provides a dyeing and finishing method for basalt fiber core knitted fabric. The basalt fiber core knitted fabric includes a basalt fiber core and a polyester covering layer surrounding the basalt fiber core. The dyeing and finishing method includes the following steps: performing a preliminary setting treatment on the greige fabric, controlling the preliminary setting temperature at 180-200℃; dyeing the pre-set fabric, the dyeing including staged temperature increases: first, increasing the temperature to 90℃ at 1.5-2.0℃ / min, then increasing the temperature to 130℃ at 0.5-1.0℃ / min and holding at that temperature; after dyeing, using a rubber... The rubber blanket pre-shrinking machine pre-shrinks the fabric, controlling the wet-feed liquid ratio at 15%-20%, the heating roller temperature at 110-120℃, the rubber blanket pressure at 1.2-1.5MPa, and the pre-shrinking overfeed at 6%-12%. After pre-shrinking, the fabric undergoes finishing, with a warp overfeed of 8%-12% and a weft tension of 0.1-0.2N / cm. At the end of the finishing process, cold air at 20-25℃ and a wind speed of 8-10m / s is used for cooling, and the finishing process is repeated 2-3 times. Compared to conventional dyeing and finishing methods for basalt yarn knitted fabrics, this dyeing and finishing method can improve the problems of poor fabric smoothness and itchy feeling after dyeing and finishing.

The application belongs to the technical field of image processing, and provides an animation video frame rate adjustment method and system based on artificial intelligence, which comprises the following steps: obtaining an initial optical flow field through pixel-level optical flow calculation, combining optical flow amplitude and local spatial variance to calculate motion saliency features, generating a binary motion gating mask according to the motion saliency features, dividing a picture into a static background area and an effective motion area, generating corresponding intermediate frame pixels for the effective motion area by using a deep learning frame insertion network, not performing network reasoning for the static background area, directly mapping original image corresponding position pixels as intermediate frame pixels, finally splicing the pixels of the two types of areas, outputting a complete interpolation frame and inserting the original video sequence, and realizing frame rate improvement.