8962
社区成员
Advances in Feature Selection for Data and Pattern Recognition下载
这是关于特征选择和模式识别的电子书，高清，最新版本，经典著作，英文版
相关下载链接：//download.csdn.net/download/cgs425449830/10634610?utm_source=bbsseo
相关下载链接：//download.csdn.net/download/cgs425449830/10634610?utm_source=bbsseo
...全文
当前发帖距今超过3年，不再开放新的回复
发表回复
Advances in Feature Selection for Data and Pattern Recognition This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection ...
[PED07]Feature Selection for Clustering:A Review聚类特征选择综述 文章目录0.1 introduction介绍0.1.1 Clustering 聚类0.1.2 Feature Selection Models 特征选择模型0.1.3 Feature Selection for Clustering 聚类的特征选择0.1.3.1 Filter Model0.1.3.2 Wrapper Mode0.1.3.3 Hybrid ...
Advances in Neural Networks Computational and Theoretical Issues This research book aims to provide the reader with a selection ...are proposed, which include the data selection and preparation step, the feature extraction phase, and the pattern recognition procedures
【Paper】HAR：Deep Convolutional and LSTM RNN for Multimodal Wearable Activity Recognition Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: ...
【2011-2016】 NIPS汇总 - Advances in Neural Information Processing Systems Advances in Neural Information Processing Systems 24 (NIPS 2011) The papers below appear in Advances in Neural Information Processing Systems 24 edited by J. Shawe-Taylor and R.S. Zemel and ...
A NOVEL DEEP FEATURE FUSION NETWORK FOR REMOTE SENSING SCENE CLASSIFICATION（论文翻译） 作者：Yangyang Li*, Senior Member, IEEE, Qi Wang, Xiaoxu Liang and Licheng Jiao, Fellow, IEEE 单位及邮箱：Key Laboratory of Intelligent Perception and Image Understanding of Ministry of E...
The Science of Pattern Recognition Achievements and Perspectives The Science of Pattern Recognition Achievements and Perspectives Robert P.W. Duin1 and El˙zbieta P_ ekalska2 1 ICT group, Faculty of Electr. Eng., Mathematics and Computer Science Delft ...
Deep Learning for Remote Sensing Data Deep Learning for Remote Sensing Data_A technical tutorial on the state of the art一，Abstract二，ADVANTAGES OF REMOTE SENSING METHODS遥感方法的优点注释2：Handcrafted features注释1：discriminability ...
ECCV2020 Learning Data Augmentation Strategies for Object Detection ECCV2020 Learning Data Augmentation Strategies for Object Detection论文翻译 摘要 1.介绍 2.相关工作 3.方法 4.结果 4.1 学习一个数据增强策略 4.2 学习的增强策略系统地改进了目标检测 4.3 利用学习的增强策略...
Data Driven Methods for MRI Reconstruction based data uh to to reduce how much time you spend collecting that ...data adaptive methods uh for choosing which locations in k space to sample and and there's been a very recent uh trend towards uh ...
计算机视觉论文-2021-05-31 本专栏是计算机视觉方向论文收集积累，时间：2021年5月28日，来源：paper ...1, TITLE:Type III Solar Radio Burst Detection and Classification: A Deep Learning Approach AUTHORS: Jeremiah Scully ; Ronan F...
UCB Visual Object and Activity Recognition, Class CS 294-43 UCB Visual Object and Activity Recognition, Class CS 294-43 Prof. Trevor Darrell, trevor@eecs.berkeley.edu, Spring 2011 This course wil
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space翻译 Abstract 以前很少有研究点集深度学习的著作。...通过利用度量空间距离，我们的网络能够在不断增加的上下文范围内学习局部特征。进一步观察到点集通常以不同的密度采样，这导致在均匀密度上训练的网络的性
深度 | 香港中文大学（深圳）张大鹏教授：生物特征识别的新进展 | CCF-GAIR 2019 – “Feature selection and analysis on correlated gas sensor data with recursive feature elimination,” Sensors & Actuators: B. Chemical, 212, 353-363. 2015(气味分析) – “Design of breath analysis...
计算机视觉论文-2021-08-03 本专栏是计算机视觉方向论文收集积累，时间：2021年8月3日，来源：paper ...1, TITLE:Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction AUTHORS: FANG ZHENG et. al. CATEGORY: cs.A...
计算机视觉论文-2021-09-14 本专栏是计算机视觉方向论文收集积累，时间：2021年9月14日，来源：paper ...1, TITLE:COSMic: A Coherence-Aware Generation Metric for Image Descriptions AUTHORS: MERT ?NAN et. al. CATEGORY: cs.CL [cs.CL...
图像处理与计算机视觉基础，经典以及最近发展 Pattern Recognition and Machine Learning Bishop: Christopher M. Springer 模式识别: 西奥多里德斯著 Pattern Classification: Richard O. Duda etc. Statistical Pattern Recognition: Andrew R. Webb etc. ...
