title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½Ð° Ð¼Ð°Ð»Ð¾Ð¹ Ð²ÑÐ±Ð¾ÑÐºÐµ ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸ÐµÐ¼ Ð¾Ð±Ð»Ð°ÑÑÐµÐ¹ Ð´Ð°Ð½Ð½Ñ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: Design of an algorithm for solving few-shot learning problems by converging data areas
Creators: name: Ð¨Ð°Ð³Ð²Ð°Ð»Ð¸ÐµÐ², ÐÐ¸ÑÐ°Ð¸Ð»
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: 2022
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ð½Ð° Ð¼Ð°Ð»ÑÑ Ð²ÑÐ±Ð¾ÑÐºÐ°Ñ
machine learning
artificial intelligence
deep learning
metric learning
few-shot learning

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: "Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° ÑÐµÑÐµÐ½Ð¸ÑÂ Ð·Ð°Ð´Ð°Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½Ð° Ð¼Ð°Ð»Ð¾Ð¹ Ð²ÑÐ±Ð¾ÑÐºÐµ ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸ÐµÐ¼ Ð¾Ð±Ð»Ð°ÑÑÐµÐ¹ Ð´Ð°Ð½Ð½ÑÑ".Â ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸, Ð¿Ð¾Ð´Ð´ÐµÑÐ¶Ð¸Ð²Ð°ÑÑÐ¸Ñ ÑÑÐµÐ½Ð°ÑÐ¸Ð¹ Ð´Ð¾Ð±Ð°Ð²Ð»ÐµÐ½Ð¸Ñ Ð½Ð¾Ð²ÑÑ ÐºÐ»Ð°ÑÑÐ¾Ð²: Ð¼Ð¾Ð´ÐµÐ»Ñ, Ð¾Ð±ÑÑÐµÐ½Ð½Ð°Ñ Ð¸Ð·Ð½Ð°ÑÐ°Ð»ÑÐ½Ð¾ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸ÑÑ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð½Ð° Ð½Ð°ÑÐ°Ð»ÑÐ½ÑÑ ÐºÐ»Ð°ÑÑÐ°Ñ, Ð´Ð¾Ð»Ð¶Ð½Ð° Ð¿Ð¾Ð´Ð´ÐµÑÐ¶Ð¸Ð²Ð°ÑÑ Ð´Ð¾Ð±Ð°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð½Ð¾Ð²ÑÑ ÐºÐ»Ð°ÑÑÐ¾Ð², Ð¿ÑÑÐµÐ¼ Ð´Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½Ð° Ð¼Ð°Ð»Ð¾Ð¼ Ð½Ð°Ð±Ð¾ÑÐµ Ð´Ð°Ð½Ð½ÑÑ, ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²ÑÑÑÐµÐ¼ Ð½Ð¾Ð²ÑÐ¼ ÐºÐ»Ð°ÑÑÐ°Ð¼. ÐÐ´Ð½Ð¸Ð¼ Ð¸Ð· Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð² ÑÐµÑÐµÐ½Ð¸Ñ ÑÑÐ¾Ð¹ Ð·Ð°Ð´Ð°ÑÐ¸ ÑÐ²Ð»ÑÐµÑÑÑ Ð¼ÐµÑÐ¾Ð´ Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ ProxyNormSoftmax, ÐºÐ¾ÑÐ¾ÑÑÐ¹ Ð¾ÑÐ½Ð¾Ð²Ð°Ð½ Ð½Ð° Ð¸Ð´ÐµÐµ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ Ð¾ÑÐ¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾Ð´Ð½ÑÑ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð² Ð¿ÑÐ¾ÑÑÑÐ°Ð½ÑÑÐ²Ð¾ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² ÑÐ°ÐºÐ¸Ð¼ Ð¾Ð±ÑÐ°Ð·Ð¾Ð¼, ÑÑÐ¾Ð±Ñ ÐºÐ»Ð°ÑÑÑ ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð»Ð¸ ÐºÐ»Ð°ÑÑÐµÑÑ Ñ ÐµÐ´Ð¸Ð½ÑÑÐ²ÐµÐ½Ð½ÑÐ¼ ÑÐµÐ½ÑÑÐ¾Ð¼ Ð² Ð¿ÑÐ¾ÑÑÑÐ°Ð½ÑÑÐ²Ðµ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð². Ð ÑÐ°Ð±Ð¾ÑÐµ Ð¿ÑÐµÐ´Ð»Ð°Ð³Ð°ÑÑÑÑ Ð¼Ð¾Ð´Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ProxyNormSoftmax, Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð½ÑÐµ Ð½Ð° Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ð¸ Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¸Ñ ÑÐµÐ½ÑÑÐ¾Ð² ÐºÐ»Ð°ÑÑÐµÑÐ¾Ð² ÐºÐ»Ð°ÑÑÐ¾Ð². Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²Ð° ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ Ð¿ÑÐ¸Ð¼ÐµÐ½Ð¸ÑÐµÐ»ÑÐ½Ð¾ Ðº Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸ÑÐ¼ Ð½Ð° Ð½Ð°Ð±Ð¾ÑÐ°Ñ Ð´Ð°Ð½Ð½ÑÑ CARS-196 Ð¸ UCSD-200-2011 Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ ProxyNormSoftmax Ð¸ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð½ÑÐ¼Ð¸ Ð¼Ð¾Ð´Ð¸ÑÐ¸ÐºÐ°ÑÐ¸ÑÐ¼Ð¸ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð½Ð¾, ÑÑÐ¾ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð½ÑÐµ Ð¼Ð¾Ð´Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ðµ Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¾ ÑÐµÐ½ÑÑÐ¾Ð² ÐºÐ»Ð°ÑÑÐµÑÐ¾Ð² ÐºÐ»Ð°ÑÑÐ¾Ð² Ð´Ð°ÑÑ Ð»ÑÑÑÐµÐµ ÐºÐ°ÑÐµÑÑÐ²Ð¾ ÑÐµÑÐµÐ½Ð¸Ñ.
description: The subject of the graduate qualification work is Â«Design of an algorithm forÂ solving few-shot learning problems by converging data areasÂ». This thesis is devoted to the design of deep learning models for solving classification problems that support the scenario of adding new classes: a model initially trained to classify on initial classes should support adding new classes by additionally training on a small dataset corresponding to new classes. One of the approaches for solving this problem is the ProxyNormSoftmax metric learning method, which is based on the idea of constructing a mapping of input objects into the feature space in such a way that classes form clusters with a single center in the feature space. In this work we propose modifications of ProxyNormSoftmax based on the construction of several centers of class clusters. As a result of studying the quality of solving the problem in relation to images on the CARS-196 and UCSD-200-2011 datasets by the ProxyNormSoftmax method and the proposed modifications, it has been shown that the proposed modifications using several class cluster centers provide the better solution quality.