4.7 Article

Transferable Convolutional Neural Network for Weed Mapping With Multisensor Imagery

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Geochemistry & Geophysics

More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

Danfeng Hong et al.

Summary: This study introduces a general multimodal deep learning (MDL) framework for the classification and identification challenges in geoscience and remote sensing. By investigating a special case of multi-modality learning (MML), the study presents five fusion strategies and demonstrates how to train deep networks and build network architectures effectively. Experimental results on two different multimodal RS data sets confirm the efficiency and advantages of the proposed MDL framework.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)

Article Geochemistry & Geophysics

Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

Renlong Hang et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2020)

Article Agriculture, Multidisciplinary

Analysis of transfer learning for deep neural network based plant classification models

Aydin Kaya et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)

Article Geochemistry & Geophysics

Analysis of Spectral Bands and Spatial Resolutions for Weed Classification Via Deep Convolutional Neural Network

Adnan Farooq et al.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2019)

Article Computer Science, Artificial Intelligence

A novel deep learning based framework for the detection and classification of breast cancer using transfer learning

SanaUllah Khan et al.

PATTERN RECOGNITION LETTERS (2019)

Article Geography, Physical

Learnable manifold alignment (LeMA): A semi-supervised cross-modality learning framework for land cover and land use classification

Danfeng Hong et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2019)

Article Computer Science, Information Systems

S-DenseNet: A DenseNet Compression Model Based on Convolution Grouping Strategy Using Skyline Method

Changyong Yu et al.

IEEE ACCESS (2019)

Article Environmental Sciences

End-to-End Airplane Detection Using Transfer Learning in Remote Sensing Images

Zhong Chen et al.

REMOTE SENSING (2018)

Article Agriculture, Multidisciplinary

AgroAVNET for crops and weeds classification: A step forward in automatic farming

Trupti R. Chavan et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)

Article Multidisciplinary Sciences

Mid-level visual features underlie the high-level categorical organization of the ventral stream

Bria Long et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)

Article Robotics

weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming

Inkyu Sa et al.

IEEE ROBOTICS AND AUTOMATION LETTERS (2018)

Article Engineering, Electrical & Electronic

Hyperspectral Image Superresolution by Transfer Learning

Yuan Yuan et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2017)

Article Remote Sensing

Scene classification for aerial images based on CNN using sparse coding technique

Abdul Qayyum et al.

INTERNATIONAL JOURNAL OF REMOTE SENSING (2017)

Article Computer Science, Artificial Intelligence

How deep learning extracts and learns leaf features for plant classification

Sue Han Lee et al.

PATTERN RECOGNITION (2017)

Article Robotics

Mixtures of Lightweight Deep Convolutional Neural Networks: Applied to Agricultural Robotics

Chris McCool et al.

IEEE ROBOTICS AND AUTOMATION LETTERS (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Densely Connected Convolutional Networks

Gao Huang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Article Geochemistry & Geophysics

Target Classification Using the Deep Convolutional Networks for SAR Images

Sizhe Chen et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2016)

Article Computer Science, Artificial Intelligence

Learning Hierarchical Features for Scene Labeling

Clement Farabet et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2013)

Article Computer Science, Artificial Intelligence

Computer vision based methods for detecting weeds in lawns

Ukrit Watchareeruetai et al.

MACHINE VISION AND APPLICATIONS (2006)