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综述：基于深度学习的文本分类 --《Deep Learning Based Text Classification: A Comprehensive Review》总结(一)

文章目录综述：基于深度学习的文本分类《Deep Learning Based Text Classification: A Comprehensive Review》论文总结(一) 总结 1.Introduction 文本分类任务 2.

深度文本 learning deep Based

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变化检测综述 Deep learning for change detection in remote sensing images: comprehensive review and me

Deep learning for change detection in remote sensing images: comprehensive review and meta-analysis 摘要深度学习（DL）算法被认为是过

change Detection deep learning Remote

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【论文泛读】Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks

Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks [2018-SIGKDD] 本文是我在上一篇泛读

泛读论文 embedding easing learning

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分层强化学习综述：Hierarchical reinforcement learning: A comprehensive survey

论文名称：Hierarchical reinforcement learning: A comprehensive survey 论文发表期刊：ACM Computing Surveys 期刊影响因子：10.282（2022年）论文作者：

Reinforcement Hierarchical learning Survey Comprehensive

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Graph Structure Learning

1 《Graph Structure Estimation Neural Networks》—— WWW 2021 论文 2 《Learning Discrete Structures for Graph Neural Networks

Graph Structure learning

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Prompt Learning详解

现阶段NLP最火的两个idea 一个是对比学习（contrastive learning）另一个就是 prompt prompt 说简单也很简单看了几篇论文之后发现其实就是构建一个语言模板但是仔细想想又觉得复杂总感觉里面还有很多

详解 Prompt learning

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显著性目标检测之Learning to Promote Saliency Detectors

Learning to Promote Saliency Detectors论文阅读旧文重发 https:githublartpangMachine-Deep-Learning 缩写标注: SD: Saliency Detecti

目标 learning promote Saliency Detectors

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【论文翻译】Deep Recurrent Q-Learning for Partially Observable MDPs

部分可观察MDP的深度循环Q学习摘要：Deep Reinforcement Learning已经为复杂的任务提供了熟练的控制器。然而，这些控制器具有有限的存储器并且依赖于能够在每个决策点处感知

论文 Recurrent deep learning Observable

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Deep Recurrent Q-Learning for Partially Observable MDPs翻译

摘要深度强化学习已经为复杂任务提供了精准的控制器。但是，这些控制器的内存有限，并且依赖于能够在每个决策点感知完整的游戏画面。为了解决这些缺点，本文研究了用循环LSTM替换卷

learning Recurrent deep MDPs Observable

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Deep Recurrent Q-Learning for Partially Observable MDPs（DRQN）

Abstract 深度RL已经为复杂的任务提供了精通的控制器。但是，这些控制器的内存有限，并且依赖于能够在每个决策点感知完整的游戏画面。为了解决这些缺点，本文研究了用循环LS

learning Recurrent deep Partially DRQN

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IntelliLight: a Reinforcement Learning Approach for Intelligent Traffic Light Control 论文阅读

IntelliLight 全文脉络概述1、本文贡献1）Experiments with real traffic data.2）Interpretations of the policy.3&am

论文 learning Approach IntelliLight Reinforcement

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论文笔记：A Robust Learning Approach to Domain Adaptive Object Detection

论文地址：https:ieeexplore.ieeedocument9008383 源码地址：https:githubGabriel-Maciasrobust_frcnn 1 以前的方法在目标域中有

笔记论文 learning Robust Approach

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DeepSurf: A surface-based deep learning approach for theprediction of ligand binding sites on prote

论文解读：DeepSurf：一种基于表面的深度学习方法预测蛋白质上的配体结合位点期刊：Bioinformatics 中科院分区;Q1 影像因子&#xff1a

deep learning Based DeepSurf Surface

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ACTIVE LEARNING FOR CONVOLUTIONAL NEURAL NETWORKS : A CORE -SET APPROACH阅读笔记

ICLR 2018的一篇文献，看Multiple Instance Active Learning for Object Detection的在评价性能的时候看到了这个模型，由于是第一次接触主动学

笔记 Convolutional Neural active learning

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文献阅读 - A Discriminative Feature Learning Approach for Deep Face Recognition

A Discriminative Feature Learning Approach for Deep Face Recognition Y. Wen, K. Zhang, Z. Li, & Y. Qiao, A Discrimin

文献 feature Discriminative learning Recognition

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A Hybrid Approach to Privacy-Preserving Federated Learning

背景差分隐私(Differential Privacy)隐私其实是一个很微妙的定义，在机器学习领域，这个定义变得更加模糊，考虑以下场景：高德地图曾

Privacy Approach Hybrid learning Federated

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《FL-MSRE: A Few-Shot Learning based Approach to Multimodal Social RelationExtraction》

知识点了解few-shot learning: 理解1，理解2 欧式距离Contribution We present multimodal social relation datasets, which

Shot learning fl MSRE Based

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A Sim2Real Deep Learning Approach for theTransformation of Images from Multiple Vehicle-Mounted Cam

IPM变换建立image到BEV平面的映射关系但是IPM变换的前提假设是世界是一个平坦的平面，但是3D物体是有高度的，或者当路面出现起伏的时候就会违反这一假设，导致出现目标物

Approach theTransformation learning Sim2Real deep

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A Spatiotemporal Deep Learning Approach for Unsupervised Anomaly Detection in Cloud Systems

《A Spatiotemporal Deep Learning Approach for Unsupervised Anomaly Detection in Cloud Systems》-2020-TNNLS-B类背景整体结构GraphL

learning Approach Spatiotemporal deep Unsupervised

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ECCV 2016 A Deep Learning-Based Approach to Progressive Vehicle Re-identification

文章目录摘要 1.引言 2.相关工作 3.提出的方法（PROVID） 3.1 概述 3.2 外观特征提取（by CNN） 3.3 基于SNN的车牌识别 3.4 基于时空关系重排序 4.实验 4.1 数据集 4.2 实验设置 4.3 车牌验

deep learning ECCV Based Vehicle

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