度量学习/对比学习入门: 论文阅读笔记-Deep Metric Learning: A Survey Derec live and let live 来自专栏 · 深度视觉与自然语言探究 471 人赞同了该文章 Outline: 度量学习 直接度量 转换后度量 深度度量学习 样本挖掘 模型结构 损失函数 总结 本文从传统的度量学习一路讲到近些年提出的深度度量学习,是入门度量学...
度量学习是从数据中学习距离方法，以区分相似与不相似对象。其核心目标是让相似对象之间的距离小，不相似对象之间的距离大。度量学习可以分为基于原始特征空间的方法与基于投影矩阵的方法。原始特征空间方法，如KNN算法，直接基于欧氏距离计算对象相似性。投影矩阵方法，如马氏距离，通过投影矩阵转换特征空间后再...
Metric learning aims to measure the similarity among samples while using an optimal distance metric for learning tasks. Metric learning methods, which generally use a linear projection, are limited in solving real-world problems demonstrating non-linear characteristics. Kernel approaches are utilized in ...
A survey on metric learning for feature vectors and structured data (Figure 1) Deep metric learning using Triplet network (triplet loss) FaceNet: A Unified Embedding for Face Recognition and Clustering (semi-hard,L2-normalization) Deep Metric Learning via Lifted Structured Feature Embedding (Lifted ...
深度学习图像分割综述📖 Image Segmentation Using Deep Learning: A Survey 原文连接:https://arxiv.org/pdf/2001.05566.pdf Abstract 图像分割应用包括场景理解、医学图像分析、机器人感知、视频监控
《Deep Long-Tailed Learning: A Survey》 深度长尾学习: 调查 作者 Yifan Zhang、Bingyi Kang、Bryan Hooi、Shuicheng Yan(IEEE Fellow)和 Jiashi Feng 来自新加坡国立大学计算机学院、字节跳动 AI Lab 和 SEA AI Lab 初读 摘要 长尾类别不平衡(long-tailed class imbalance): ...
Ranked List Loss for Deep Metric Learning | 论文分享 0% 展开列表 一手实测Gemini 2.5 Pro:编程能力像开盲盒,时而惊艳时而抽风 2小时前 AI测评 北大、清华、UvA、CMU等联合发布:大模型逻辑推理能力最新综述 2小时前 IJCAI 2025 Survey Track ICML 2025 | 视频生成模型无损加速两倍,秘诀竟然是「抓住attention的时...
in the "Discussion of surveyed works" section, summarize all of the surveyed deep learning methods and the details of their corresponding data sets. This survey provides the most current analysis of deep learning methods for addressing class imbalance, summarizing and comparing all related work to ...
data sampling and cost-sensitive learning, prove to be applicable in deep learning, while more advanced methods that exploit neural network feature learning abilities show promising results. The survey concludes with a discussion that highlights various gaps in deep learning from class imbalanced data ...
Model complexity is a fundamental problem in deep learning. In this paper, we conduct a systematic overview of the latest studies on model complexity in de