On the public citation graph

Optimized Horticulture Species Identification and Crown Segmentation Using Multi-Modal Vision Transformers and Uav Imagery

https://doi.org/10.2139/ssrn.5370592
0 signed · 78 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01228-1_26openalex-snapshot
Unified Perceptual Parsing for Scene Understanding
inferredcites →https://doi.org/10.1007/978-3-030-98981-1_12openalex-snapshot
Geospatial Applications in Inventory of Horticulture Plantations
inferredcites →https://doi.org/10.1007/978-3-031-82156-1_9openalex-snapshot
Semantic Segmentation of Unmanned Aerial Vehicle Remote Sensing Images Using SegFormer
inferredcites →https://doi.org/10.1007/s10457-024-01042-2openalex-snapshot
Geospatial assessment of agroforestry land use systems using very high-resolution satellite images and artificial intelligence
inferredcites →https://doi.org/10.1007/s10531-019-01772-1openalex-snapshot
Pattern of distribution of angiosperm plant richness along latitudinal and longitudinal gradients of India
inferredcites →https://doi.org/10.1007/s11676-013-0396-zopenalex-snapshot
Characterizing Shorea robusta communities in the part of Indian Terai landscape
inferredcites →https://doi.org/10.1016/j.atech.2022.100068openalex-snapshot
Detecting olive grove abandonment with Sentinel-2 and machine learning: The development of a web-based tool for land management
inferredcites →https://doi.org/10.1016/j.compag.2024.109530openalex-snapshot
Oil palm tree detection in UAV imagery using an enhanced RetinaNet
inferredcites →https://doi.org/10.1016/j.compag.2024.109540openalex-snapshot
A novel multitask transformer deep learning architecture for joint classification and segmentation of horticulture plantations using very High-Resolution satellite imagery
inferredcites →https://doi.org/10.1016/j.ecoinf.2022.101900openalex-snapshot
A new synergistic approach for Sentinel-1 and PALSAR-2 in a machine learning framework to predict aboveground biomass of a dense mangrove forest
inferredcites →https://doi.org/10.1016/j.ecolind.2024.112110openalex-snapshot
Spectral–Spatial transformer-based semantic segmentation for large-scale mapping of individual date palm trees using very high-resolution satellite data
inferredcites →https://doi.org/10.1016/j.foreco.2020.118397openalex-snapshot
Individual tree detection and species classification of Amazonian palms using UAV images and deep learning
inferredcites →https://doi.org/10.1016/j.isprsjprs.2020.10.015openalex-snapshot
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks
inferredcites →https://doi.org/10.1016/j.isprsjprs.2024.02.010openalex-snapshot
Supervised terrestrial to airborne laser scanner model calibration for 3D individual-tree attribute mapping using deep neural networks
inferredcites →https://doi.org/10.1016/j.jag.2013.05.017openalex-snapshot
A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales
inferredcites →https://doi.org/10.1016/j.rse.2006.04.004openalex-snapshot
Resolution dependent errors in remote sensing of cultivated areas
inferredcites →https://doi.org/10.1016/j.rse.2016.08.013openalex-snapshot
Review of studies on tree species classification from remotely sensed data
inferredcites →https://doi.org/10.1016/j.rse.2018.03.023openalex-snapshot
Land cover and land use change analysis using multi-spatial resolution data and object-based image analysis
inferredcites →https://doi.org/10.1016/j.rse.2021.112322openalex-snapshot
Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks
inferredcites →https://doi.org/10.1016/j.rse.2022.113143openalex-snapshot
Individual tree segmentation and tree species classification in subtropical broadleaf forests using UAV-based LiDAR, hyperspectral, and ultrahigh-resolution RGB data
inferredcites →https://doi.org/10.1016/j.rse.2023.113485openalex-snapshot
Surveying coconut trees using high-resolution satellite imagery in remote atolls of the Pacific Ocean
inferredcites →https://doi.org/10.1016/j.srs.2024.100190openalex-snapshot
A comprehensive evaluation of deep vision transformers for road extraction from very-high-resolution satellite data
inferredcites →https://doi.org/10.1016/j.ufug.2020.126634openalex-snapshot
Street tree health from space? An evaluation using WorldView-3 data and the Washington D.C. Street Tree Spatial Database
inferredcites →https://doi.org/10.1016/s0169-5347(03)00070-3openalex-snapshot
Remote sensing for biodiversity science and conservation
inferredcites →https://doi.org/10.1038/s41598-019-53797-9openalex-snapshot
Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery
inferredcites →https://doi.org/10.1038/s41598-020-79653-9openalex-snapshot
Explainable identification and mapping of trees using UAV RGB image and deep learning
inferredcites →https://doi.org/10.1038/s41598-024-67186-4openalex-snapshot
Transformer-based land use and land cover classification with explainability using satellite imagery
inferredcites →https://doi.org/10.1038/s41598-024-72669-5openalex-snapshot
An open dataset for individual tree detection in UAV LiDAR point clouds and RGB orthophotos in dense mixed forests
inferredcites →https://doi.org/10.1038/s41598-025-94544-7openalex-snapshot
Enhanced hybrid CNN and transformer network for remote sensing image change detection
inferredcites →https://doi.org/10.1080/01431160512331314083openalex-snapshot
Support vector machines for classification in remote sensing
inferredcites →https://doi.org/10.1080/01431161.2020.1857877openalex-snapshot
Parametric study of convolutional neural network based remote sensing image classification
inferredcites →https://doi.org/10.1080/01431161.2024.2377837openalex-snapshot
Tree species classification based on PointNet++ deep learning and true- colour point cloud
inferredcites →https://doi.org/10.1109/aero55745.2023.10115761openalex-snapshot
SeMask-Mask2Former: A Semantic Segmentation Model for High Resolution Remote Sensing Images
inferredcites →https://doi.org/10.1109/agro-geoinformatics59224.2023.10233389openalex-snapshot
SegFormer-Based Cotton Planting Areas Extraction from High-Resolution Remote Sensing Images
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-snapshot
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.660openalex-snapshot
Pyramid Scene Parsing Network
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00135openalex-snapshot
Masked-attention Mask Transformer for Universal Image Segmentation
inferredcites →https://doi.org/10.1109/iccv48922.2021.00986openalex-snapshot
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
inferredcites →https://doi.org/10.1109/icetci57876.2023.10177013openalex-snapshot
UPerNet with ConvNeXt for Semantic Segmentation
inferredcites →https://doi.org/10.1109/icip46576.2022.9897888openalex-snapshot
Maskformer with Improved Encoder-Decoder Module for Semantic Segmentation of Fine-Resolution Remote Sensing Images
inferredcites →https://doi.org/10.1109/icme52920.2022.9859720openalex-snapshot
CAT: Cross Attention in Vision Transformer
inferredcites →https://doi.org/10.1109/jstars.2020.3005403openalex-snapshot
Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities
inferredcites →https://doi.org/10.1109/tgrs.2023.3266057openalex-snapshot
TSCMDL: Multimodal Deep Learning Framework for Classifying Tree Species Using Fusion of 2-D and 3-D Features
inferredcites →https://doi.org/10.12928/telkomnika.v23i1.26244openalex-snapshot
Deep learning-based palm tree detection in unmanned aerial vehicle imagery with Mask R-CNN
inferredcites →https://doi.org/10.1890/070152openalex-snapshot
Airborne spectranomics: mapping canopy chemical and taxonomic diversity in tropical forests
inferredcites →https://doi.org/10.20546/ijcmas.2019.808.007openalex-snapshot
Coconut Inventory and Mapping Using Object Oriented Classification
inferredcites →https://doi.org/10.32604/cmc.2024.052597openalex-snapshot
ConvNeXt-UperNet-Based Deep Learning Model for Road Extraction from High-Resolution Remote Sensing Images
inferredcites →https://doi.org/10.3390/agriculture15030326openalex-snapshot
Precision Agriculture: Temporal and Spatial Modeling of Wheat Canopy Spectral Characteristics
inferredcites →https://doi.org/10.3390/drones7020093openalex-snapshot
Large-Scale Date Palm Tree Segmentation from Multiscale UAV-Based and Aerial Images Using Deep Vision Transformers
inferredcites →https://doi.org/10.3390/electronics12051111openalex-snapshot
Swin-UperNet: A Semantic Segmentation Model for Mangroves and Spartina alterniflora Loisel Based on UperNet
inferredcites →https://doi.org/10.3390/f15020293openalex-snapshot
Individual Tree Species Identification for Complex Coniferous and Broad-Leaved Mixed Forests Based on Deep Learning Combined with UAV LiDAR Data and RGB Images
inferredcites →https://doi.org/10.3390/jimaging7110241openalex-snapshot
Tree Crowns Segmentation and Classification in Overlapping Orchards Based on Satellite Images and Unsupervised Learning Algorithms
inferredcites →https://doi.org/10.3390/math12050765openalex-snapshot
Mask2Former with Improved Query for Semantic Segmentation in Remote-Sensing Images
inferredcites →https://doi.org/10.3390/rs10010099openalex-snapshot
Remote Sensing and Cropping Practices: A Review
inferredcites →https://doi.org/10.3390/rs12071070openalex-snapshot
Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks
inferredcites →https://doi.org/10.3390/rs13030516openalex-snapshot
Vision Transformers for Remote Sensing Image Classification
inferredcites →https://doi.org/10.3390/rs13112027openalex-snapshot
Species-Level Classification and Mapping of a Mangrove Forest Using Random Forest—Utilisation of AVIRIS-NG and Sentinel Data
inferredcites →https://doi.org/10.3390/rs14030476openalex-snapshot
Transformer for Tree Counting in Aerial Images
inferredcites →https://doi.org/10.3390/rs14092015openalex-snapshot
Parcel-Level Mapping of Horticultural Crop Orchards in Complex Mountain Areas Using VHR and Time-Series Images
inferredcites →https://doi.org/10.3390/rs14112621openalex-snapshot
Machine Learning Classification of Fused Sentinel-1 and Sentinel-2 Image Data towards Mapping Fruit Plantations in Highly Heterogenous Landscapes
inferredcites →https://doi.org/10.3390/rs15102596openalex-snapshot
Application of Machine Learning to Tree Species Classification Using Active and Passive Remote Sensing: A Case Study of the Duraer Forestry Zone
inferredcites →https://doi.org/10.3390/rs15174140openalex-snapshot
Optimized Extraction Method of Fruit Planting Distribution Based on Spectral and Radar Data Fusion of Key Time Phase
inferredcites →https://doi.org/10.3390/rs16142547openalex-snapshot
Remote Sensing Classification and Mapping of Forest Dominant Tree Species in the Three Gorges Reservoir Area of China Based on Sample Migration and Machine Learning
inferredcites →https://doi.org/10.3390/rs16173207openalex-snapshot
High-Precision Mango Orchard Mapping Using a Deep Learning Pipeline Leveraging Object Detection and Segmentation
inferredcites →https://doi.org/10.3390/rs16203836openalex-snapshot
Tree Species Classification from UAV Canopy Images with Deep Learning Models
inferredcites →https://doi.org/10.3390/rs17050790openalex-snapshot
Mapping Urban Tree Species by Integrating Canopy Height Model with Multi-Temporal Sentinel-2 Data
inferredcites →https://doi.org/10.3390/rs8030166openalex-snapshot
First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe
inferredcites →https://doi.org/10.3390/rs8060445openalex-snapshot
Tree Species Classification Using Hyperspectral Imagery: A Comparison of Two Classifiers
inferredcites →https://doi.org/10.3390/rs9010022openalex-snapshot
Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images
inferredcites →https://doi.org/10.3390/s141222643openalex-snapshot
Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot
Exploiting Generative AI to Scale up Intelligent Tutoring Systems
inferredcites →https://doi.org/10.48550/arxiv.2305.14914openalex-snapshot
GAMUS: A Geometry-aware Multi-modal Semantic Segmentation Benchmark for Remote Sensing Data
inferredcites →https://doi.org/10.48550/arxiv.2306.08336openalex-snapshot
Global-Local Processing in Convolutional Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.2411.10251openalex-snapshot
Morpho-Aware Global Attention for Image Matting
inferredcites →https://doi.org/10.5194/isprsarchives-xl-8-745-2014openalex-snapshot
Object oriented classification of high resolution data for inventory of horticultural crops
inferredcites →https://doi.org/10.5772/intechopen.71049openalex-snapshot
A Review: Remote Sensing Sensors
inferredcites →https://doi.org/10.5958/0974-0112.2017.00040.8openalex-snapshot
Estimation of mango growing areas using remote sensing
inferredcites →https://doi.org/10.7717/peerj-cs.1222openalex-snapshot
Research on land cover type classification method based on improved MaskFormer for remote sensing images
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.