title: ÐÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ Ð±Ð»Ð¾ÐºÐ¾Ð² ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Coding unit classifier
Creators: name: ÐÑÐ½ Ð¦Ð·ÑÐ½Ð¸Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ
Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ðµ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸
ÐºÐ¾Ð½ÑÑÐ¾Ð»Ð¸ÑÑÐµÐ¼Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼
Ð±Ð»Ð¾Ðº ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ
machine learning
classification algorithm
classifier
classification prediction
supervised learning
algorithm
coding block

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ Ð±Ð»Ð¾ÐºÐ¾Ð² ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸ÑÂ». Ð Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½ Ð½Ð¾Ð²ÑÐ¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ (Coding unit classification algorithm, CUCL) Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð¼ Ð¾Ð±ÑÑÐµÐ½Ð¸Ð¸. CUCL Ð²Ð´Ð¾ÑÐ½Ð¾Ð²Ð»ÐµÐ½ Ð±Ð»Ð¾ÐºÐ¾Ð¼ Ð´ÐµÑÐµÐ²Ð° ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ (Coding Tree Unit, CTU) Ð² Ð²ÑÑÐ¾ÐºÐ¾ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾Ðµ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð²Ð¸Ð´ÐµÐ¾Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ (High Efficiency Video Coding, HEVC ÑÐ°ÐºÐ¶Ðµ Ð¸Ð·Ð²ÐµÑÑÐ½Ð¾Ðµ ÐºÐ°Ðº H.265) [1]. ÐÐ»Ð¾Ðº Ð´ÐµÑÐµÐ²Ð° ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÐ¼ Ð±Ð»Ð¾ÐºÐ¾Ð¼ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ HEVC, Ð·Ð°Ð¼ÐµÐ½ÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð²ÑÐ¸Ð¹ÑÑ ÑÐ°Ð½ÐµÐµ Ð¼Ð°ÐºÑÐ¾Ð±Ð»Ð¾ÐºÐ¾Ð² 16x16 Ð¿Ð¸ÐºÑÐµÐ»ÐµÐ¹. CTU Ð¿Ð¾Ð²ÑÑÐ°ÐµÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð·Ð° ÑÑÐµÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±Ð»Ð¾ÑÐ½Ð¾Ð¹ ÑÑÑÑÐºÑÑÑÑ Ð¿ÐµÑÐµÐ¼ÐµÐ½Ð½Ð¾Ð³Ð¾ ÑÐ°Ð·Ð¼ÐµÑÐ°, ÐºÐ¾ÑÐ¾ÑÐ°Ñ Ð¿Ð¾Ð´ÑÐ°Ð·Ð´ÐµÐ»ÑÐµÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ðµ Ð½Ð° Ð±Ð»Ð¾ÐºÐ¸ Ð¿Ð¸ÐºÑÐµÐ»ÐµÐ¹ Ð¿ÐµÑÐµÐ¼ÐµÐ½Ð½Ð¾Ð³Ð¾ ÑÐ°Ð·Ð¼ÐµÑÐ°, ÑÑÐ¾ Ð¾Ð±ÑÑÐ½Ð¾ Ð¿Ð¾Ð²ÑÑÐ°ÐµÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð¿ÑÐ¸ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸. ÐÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ Ð±Ð»Ð¾ÐºÐ¾Ð² ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ (Coding unit classifier, CUC) Ð±ÑÐ» ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¸Ð´ÐµÐ¸ Ð±Ð»Ð¾ÐºÐ¾Ð² ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð² Ð´ÐµÑÐµÐ²Ðµ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ. ÐÐ»Ð¾ÐºÐ¸ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ (Coding unit, CU), ÑÐ¾Ð´ÐµÑÐ¶Ð°ÑÐ¸ÐµÑÑ Ð² ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐµ Ð±Ð»Ð¾ÐºÐ¾Ð² ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ, ÑÑÑÐ¾ÑÑÑÑ Ð² ÑÑÐ¸ ÑÑÐ°Ð¿Ð°: "Ð¿ÑÐµÐ´Ð²Ð°ÑÐ¸ÑÐµÐ»ÑÐ½Ð°Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ", " ÑÑÐ¾ÑÐ½ÐµÐ½Ð½Ð°Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ" Ð¸ "Ð·Ð°ÑÐ°Ð¶ÐµÐ½Ð¸Ðµ", ÐºÐ¾ÑÐ¾ÑÑÐµ ÑÐ°ÐºÐ¶Ðµ Ð¾Ð±ÑÐ°Ð·ÑÑÑ Ð¾ÑÐµÐ½ÑÐ¸Ðº. ÐÐ»Ñ Ð½Ð¾Ð²ÑÑ ÑÐ¾ÑÐµÐº Ð²ÑÐ±Ð¾ÑÐºÐ¸, Ð²Ð²Ð¾Ð´Ð¸Ð¼ÑÑ Ð² CUC, ÑÐµÐ»ÐµÐ²Ð¾Ðµ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ðµ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·ÑÐ²Ð°ÐµÑÑÑ Ð¿Ð¾ Ð±Ð»Ð¾ÐºÑ, Ðº ÐºÐ¾ÑÐ¾ÑÐ¾Ð¼Ñ Ð¾Ð½Ð¾ Ð´Ð¾Ð»Ð¶Ð½Ð¾ Ð¿ÑÐ¸Ð½Ð°Ð´Ð»ÐµÐ¶Ð°ÑÑ. ÐÑÐ¾Ð¼Ðµ ÑÐ¾Ð³Ð¾, Ð¼Ñ Ð¿ÑÐµÐ´Ð»Ð°Ð³Ð°ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´ ÑÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ ÑÑÐ¼Ð° Ð² Ð½Ð°Ð±Ð¾ÑÐµ Ð´Ð°Ð½Ð½ÑÑ Ð¸Ð»Ð¸ ÑÐ¼ÐµÐ½ÑÑÐµÐ½Ð¸Ñ Ð²Ð»Ð¸ÑÐ½Ð¸Ñ Ð²ÑÐ±ÑÐ¾ÑÐ¾Ð² Ð½Ð° Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ° Ð¿ÑÑÐµÐ¼ Ð½Ð°ÑÑÑÐ¾Ð¹ÐºÐ¸ Ð³Ð¸Ð¿ÐµÑÐ¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² CUC. Ð ÑÐ¸Ð½Ð°Ð»ÑÐ½Ð¾Ð¼ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ CUC ÑÐ¼Ð¾Ð³ Ð±ÑÑÑÑÐ¾ Ð¿Ð¾ÑÑÑÐ¾Ð¸ÑÑ Ð¾ÑÐµÐ½ÑÐ¸Ðº Ð¸ Ð´Ð¾ÑÑÐ¸ÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ &gt;0.95 Ð½Ð° ÑÐµÑÑÐ¾Ð²Ð¾Ð¼ Ð½Ð°Ð±Ð¾ÑÐµ Ð´Ð»Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ² Ð¸ ÑÐ°ÑÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ð¹ Ð½Ð°Ð±Ð¾ÑÐ¾Ð² Ð´Ð°Ð½Ð½ÑÑ ÑÐ¾ÑÐµÐº Ð²ÑÐ±Ð¾ÑÐºÐ¸. Ð Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ Ð±ÑÐ»Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¸ Ð¸ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÑ drawio, git, numpy, pandas, Matplotlib Ð¸ scikit-learn, ÑÐ·ÑÐº ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ - Python3.9, Ð° Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ ÑÑÐµÐ´ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»ÑÑ PyCharm.
description: The topic of the final qualifying work: âCoding unit classifierâ. In this paper, we propose a new algorithm, Coding unit classification algorithm (CUCL), for solving the classification prediction problem in machine learning. The algorithm is inspired by the Coding Tree Unit (CTU) in High Efficiency Video Coding (HEVC, also known as H.265). The coding tree unit is the basic encoding unit of HEVC, replacing the 16Ã16 pixel macro blocks used in the past. The coding tree unit improves the efficiency of encoding by using a variable-sized block structure that subdivides the image into variable-sized pixel blocks, which usually increases the efficiency of encoding. We developed a Coding unit classifier (CUC) based on the idea of coding units in a coding tree. The coding unit classifier contains coding units (CU) that are constructed in three steps: "pre-segmentation", "refinement segmentation" and "infection", which also form the These coding units also form the estimator. For new sample points entered into the CUC, the target value is predicted by the coding unit to which they should belong. In addition, we propose a method to eliminate noise in the dataset or reduce the impact of outliers on the classifier performance by configuring the hyperparameters of the CUC. In the final test, the CUC was able to build predictors very quickly and achieve an accuracy of &gt;0.95 for the test set for different number of sample points and sample point distributions. In this work, the following libraries and tools drawio, git, numpy, pandas, Matplotlib and scikit-learn were used, the development language was Python 3.9, and PyCharm was used as the development and testing environment.