| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A comprehensive analysis of the advances in Indian Digital Agricultural architecture
|
Balkrishna, Acharya
|
|
|
5 |
C |
p.
|
artikel
|
| 2 |
A comprehensive and systematic study in smart drip and sprinkler irrigation systems
|
Bhavsar, Drashti
|
|
|
5 |
C |
p.
|
artikel
|
| 3 |
A comprehensive review of 3D convolutional neural network-based classification techniques of diseased and defective crops using non-UAV-based hyperspectral images
|
Noshiri, Nooshin
|
|
|
5 |
C |
p.
|
artikel
|
| 4 |
A concept for application of integrated digital technologies to enhance future smart agricultural systems
|
Gebresenbet, Girma
|
|
|
5 |
C |
p.
|
artikel
|
| 5 |
A data-driven bibliometric review on precision irrigation
|
Violino, Simona
|
|
|
5 |
C |
p.
|
artikel
|
| 6 |
A deep CNN approach to detect and classify local fruits through a web interface
|
Rahman, Md.Mahbubur
|
|
|
5 |
C |
p.
|
artikel
|
| 7 |
Agricultural process data as a source for knowledge: Perspective on artificial intelligence
|
Backman, Juha
|
|
|
5 |
C |
p.
|
artikel
|
| 8 |
AgroAPI platform: An initiative to support digital solutions for agribusiness ecosystems
|
Romani, Luciana A.S.
|
|
|
5 |
C |
p.
|
artikel
|
| 9 |
A machine learning approach to predict the most and the least feed–efficient groups in beef cattle
|
Shirzadifar, Alimohammad
|
|
|
5 |
C |
p.
|
artikel
|
| 10 |
An Edge-computing flow meter reading recognition algorithm optimized for agricultural IoT network
|
Liu, Le
|
|
|
5 |
C |
p.
|
artikel
|
| 11 |
A new computer vision workflow to assess yield quality traits in bush bean (Phaseolus vulgaris L.)
|
Jollet, D.
|
|
|
5 |
C |
p.
|
artikel
|
| 12 |
AntTracker: A low-cost and efficient computer vision approach to research leaf-cutter ants behavior
|
Sabattini, Julian Alberto
|
|
|
5 |
C |
p.
|
artikel
|
| 13 |
Application of hierarchical grouping and machine learning models for classification of genotypes of Nicotiana tabacum L. with based on morphological characteristics
|
Santos, Lucas Gabriel Souza
|
|
|
5 |
C |
p.
|
artikel
|
| 14 |
Application of machine vision and convolutional neural networks in discriminating tobacco leaf maturity on mobile devices
|
Chen, Yi
|
|
|
5 |
C |
p.
|
artikel
|
| 15 |
A production capacity investment decision-making tool for the indoor vertical farming industry
|
Schulman, Ben
|
|
|
5 |
C |
p.
|
artikel
|
| 16 |
A review of three-dimensional vision techniques in food and agriculture applications
|
Xiang, Lirong
|
|
|
5 |
C |
p.
|
artikel
|
| 17 |
Assessment of health hazards of greenhouse workers considering UV exposure and thermal comfort
|
Chowdhury, Milon
|
|
|
5 |
C |
p.
|
artikel
|
| 18 |
A wearable photoplethysmography sensor for non-invasive equine heart rate monitoring
|
Miller, Morgan
|
|
|
5 |
C |
p.
|
artikel
|
| 19 |
Big data technology adoption in beef production
|
Piña, Rolando
|
|
|
5 |
C |
p.
|
artikel
|
| 20 |
BNNDC: Branched neural network for plant disease identification
|
Ahmad, Aanis
|
|
|
5 |
C |
p.
|
artikel
|
| 21 |
CLASSIM: A relational database driven crop model interface
|
Timlin, Dennis
|
|
|
5 |
C |
p.
|
artikel
|
| 22 |
Comparing forecasting models for predicting nursery mortality under field conditions using regression and machine learning algorithms
|
Magalhães, Edison S.
|
|
|
5 |
C |
p.
|
artikel
|
| 23 |
Comparison of heating modules for suspension-type multipoint temperature variability management in smart greenhouses
|
Iqbal, Md Zafar
|
|
|
5 |
C |
p.
|
artikel
|
| 24 |
Computer vision system for counting crustacean larvae by detection
|
Rothschild, Chen
|
|
|
5 |
C |
p.
|
artikel
|
| 25 |
Damage assessment of soybean and redroot amaranth plants in greenhouse through biomass estimation and deep learning-based symptom classification
|
Gómez-Zamanillo, Laura
|
|
|
5 |
C |
p.
|
artikel
|
| 26 |
Data-Driven Modelling of Soil Moisture Dynamics for Smart Irrigation Scheduling
|
Bwambale, Erion
|
|
|
5 |
C |
p.
|
artikel
|
| 27 |
Data mining approach for dry bean seeds classification
|
Macuácua, Jaime Carlos
|
|
|
5 |
C |
p.
|
artikel
|
| 28 |
Deep learning applications for oil palm tree detection and counting
|
Kipli, Kuryati
|
|
|
5 |
C |
p.
|
artikel
|
| 29 |
Design and implementation of IoT sensors for nonvisual symptoms detection on maize inoculated with Exserohilum turcicum
|
Maginga, Theofrida J.
|
|
|
5 |
C |
p.
|
artikel
|
| 30 |
Detecting tomato leaf diseases by image processing through deep convolutional neural networks
|
Hossain, Md. Iqbal
|
|
|
5 |
C |
p.
|
artikel
|
| 31 |
Developing an extreme learning machine based approach to weed segmentation in pastures
|
Ford, Jonathan
|
|
|
5 |
C |
p.
|
artikel
|
| 32 |
Development and deployment of a big data pipeline for field-based high-throughput cotton phenotyping data
|
Issac, Amanda
|
|
|
5 |
C |
p.
|
artikel
|
| 33 |
Development and evaluation of a decision support mobile application for cotton irrigation management
|
Ale, Srinivasulu
|
|
|
5 |
C |
p.
|
artikel
|
| 34 |
Development of a multi scale interactive web-GIS system to monitor farming practices: A case study in Lemnos Island, Greece
|
Avanidou, Kalliopi
|
|
|
5 |
C |
p.
|
artikel
|
| 35 |
Development of a solar powered smart irrigation control system Kit
|
Wanyama, Joshua
|
|
|
5 |
C |
p.
|
artikel
|
| 36 |
Digital technologies to remove the information asymmetry in the food market
|
Sgroi, Filippo
|
|
|
5 |
C |
p.
|
artikel
|
| 37 |
Digital twin-based intelligent fish farming with Artificial Intelligence Internet of Things (AIoT)
|
Ubina, Naomi A.
|
|
|
5 |
C |
p.
|
artikel
|
| 38 |
Direct and indirect ground estimation of leaf area index to support interpretation of NDVI data from satellite images in hedgerow olive orchards
|
Cantini, Claudio
|
|
|
5 |
C |
p.
|
artikel
|
| 39 |
Distributed Ledger Technologies for Food Sustainability indexing
|
Gkogkos, Georgios
|
|
|
5 |
C |
p.
|
artikel
|
| 40 |
Drone-based apple detection: Finding the depth of apples using YOLOv7 architecture with multi-head attention mechanism
|
S, Praveen Kumar
|
|
|
5 |
C |
p.
|
artikel
|
| 41 |
Evaluation of IoT based smart drip irrigation and ETc based system for sweet corn
|
Kumar S, Vinod
|
|
|
5 |
C |
p.
|
artikel
|
| 42 |
Exploratory analysis on drivers and barriers to Canadian prairie agricultural technology innovation and adoption
|
Lassoued, Rim
|
|
|
5 |
C |
p.
|
artikel
|
| 43 |
Factors affecting the adoption of climate-smart agriculture technologies in rice farming systems in Mali, West Africa
|
Sanogo, Kapoury
|
|
|
5 |
C |
p.
|
artikel
|
| 44 |
Federated Learning: Crop classification in a smart farm decentralised network
|
Idoje, Godwin
|
|
|
5 |
C |
p.
|
artikel
|
| 45 |
Field robotics – Economic, technical and environmental perspectives
|
Pedersen, Søren Marcus
|
|
|
5 |
C |
p.
|
artikel
|
| 46 |
Fruit fly automatic detection and monitoring techniques: A review
|
Lello, Florence
|
|
|
5 |
C |
p.
|
artikel
|
| 47 |
Generate-Paste-Blend-Detect: Synthetic dataset for object detection in the agriculture domain
|
Giakoumoglou, Nikolaos
|
|
|
5 |
C |
p.
|
artikel
|
| 48 |
High-precision multiclass classification of chili leaf disease through customized EffecientNetB4 from chili leaf images
|
Pratap, V. Krishna
|
|
|
5 |
C |
p.
|
artikel
|
| 49 |
Improving piglets health and well-being: A review of piglets health indicators and related sensing technologies
|
Sadeghi, Ehsan
|
|
|
5 |
C |
p.
|
artikel
|
| 50 |
Improving the network architecture of YOLOv7 to achieve real-time grading of canola based on kernel health
|
Thakuria, Angshuman
|
|
|
5 |
C |
p.
|
artikel
|
| 51 |
Individuality of a group: detailed walking ability analysis of broiler flocks using optical flow approach
|
van der Eijk, Jerine A.J.
|
|
|
5 |
C |
p.
|
artikel
|
| 52 |
‘In Situ’ olive ripening monitoritation by low-cost handheld NIR
|
Jiménez Márquez, A.
|
|
|
5 |
C |
p.
|
artikel
|
| 53 |
Introducing Pollenyzer: An app for automatic determination of colour diversity for corbicular pollen loads
|
Borlinghaus, Parzival
|
|
|
5 |
C |
p.
|
artikel
|
| 54 |
Irrigated corn grain yield prediction in Florida using active sensors and plant height
|
Leitão, Diego A. H. de S．
|
|
|
5 |
C |
p.
|
artikel
|
| 55 |
Is it possible to predict the methane emission intensity of Swedish dairy cows from milk spectra?
|
Mohamad Salleh, S.
|
|
|
5 |
C |
p.
|
artikel
|
| 56 |
JutePestDetect: An intelligent approach for jute pest identification using fine-tuned transfer learning
|
Talukder, Md. Simul Hasan
|
|
|
5 |
C |
p.
|
artikel
|
| 57 |
Land suitability analysis for cocoa (Theobroma cacao) production in the Sunyani municipality, Bono region, Ghana
|
Osei-Gyabaah, Augustine Prosper
|
|
|
5 |
C |
p.
|
artikel
|
| 58 |
Land use change detection using the intensity analysis at the Bosomtwe District, Ashanti Region, Ghana
|
Adjei, Vincent
|
|
|
5 |
C |
p.
|
artikel
|
| 59 |
Low Power IoT Electronics in Precision Irrigation
|
Routis, George
|
|
|
5 |
C |
p.
|
artikel
|
| 60 |
Machine learning and handcrafted image processing methods for classifying common weeds in corn field
|
Pathak, Harsh
|
|
|
5 |
C |
p.
|
artikel
|
| 61 |
Optimal use of agricultural robot in arable crop rotation: A case study from the Netherlands
|
Ørum, Jens Erik
|
|
|
5 |
C |
p.
|
artikel
|
| 62 |
Optimization of cutting torque in a laboratory setup for harvesting cabbage following an AI-based approach
|
Sarkar, Pranay
|
|
|
5 |
C |
p.
|
artikel
|
| 63 |
Optimization of irrigation timing for sprinkler irrigation system using convolutional neural network-based mobile application for sustainable agriculture
|
Singh, Naseeb
|
|
|
5 |
C |
p.
|
artikel
|
| 64 |
O2RNet: Occluder-occludee relational network for robust apple detection in clustered orchard environments
|
Chu, Pengyu
|
|
|
5 |
C |
p.
|
artikel
|
| 65 |
Performance analysis of AI-based solutions for crop disease identification, detection, and classification
|
Tirkey, Divyanshu
|
|
|
5 |
C |
p.
|
artikel
|
| 66 |
Performance evaluation of YOLO v5 model for automatic crop and weed classification on UAV images
|
Ajayi, Oluibukun Gbenga
|
|
|
5 |
C |
p.
|
artikel
|
| 67 |
PotatoPestNet: A CTInceptionV3-RS-based neural network for accurate identification of potato pests
|
Talukder, Md. Simul Hasan
|
|
|
5 |
C |
p.
|
artikel
|
| 68 |
Potentiality assessment of solar based LED light trap as pest management tool in tea (Camellia sinensis L.)
|
Al Mamun, Muhammad Rashed
|
|
|
5 |
C |
p.
|
artikel
|
| 69 |
Precision farming technologies for crop protection: A meta-analysis
|
Anastasiou, Evangelos
|
|
|
5 |
C |
p.
|
artikel
|
| 70 |
Precision farming technologies on crop protection: A stakeholders survey
|
Anastasiou, Evangelos
|
|
|
5 |
C |
p.
|
artikel
|
| 71 |
Precision spraying using variable time delays and vision-based velocity estimation
|
Sanchez, Paolo Rommel
|
|
|
5 |
C |
p.
|
artikel
|
| 72 |
Predicting bite rate of grazing cattle from accelerometry data via semi-supervised regression
|
Hu, Shuwen
|
|
|
5 |
C |
p.
|
artikel
|
| 73 |
Recovery of a salinized tomato field in a coastal polder after the 2016 Kumamoto Earthquake in Japan
|
Tokumoto, Ieyasu
|
|
|
5 |
C |
p.
|
artikel
|
| 74 |
Robustness of plant breeding systems under automated phenotyping
|
Gerullis, Maria Katharina
|
|
|
5 |
C |
p.
|
artikel
|
| 75 |
RoseTracker: A system for automated rose growth monitoring
|
Shinoda, Risa
|
|
|
5 |
C |
p.
|
artikel
|
| 76 |
Secured telemetry based on time-variant sensing matrix – An empirical study of spectroscopic profiling
|
Zhang, Yinsheng
|
|
|
5 |
C |
p.
|
artikel
|
| 77 |
Sensor-based Safety Alarm System for Injury Prevention in Chaff cutter machine
|
Asha, K.R.
|
|
|
5 |
C |
p.
|
artikel
|
| 78 |
Smartphone-based spectroscopy as a tool to estimate soil attributes for the citizen science concept
|
Gupta, Sharad Kumar
|
|
|
5 |
C |
p.
|
artikel
|
| 79 |
Soil and satellite remote sensing variables importance using machine learning to predict cotton yield
|
Carneiro, Franciele Morlin
|
|
|
5 |
C |
p.
|
artikel
|
| 80 |
Solutions and prospects for digital documentation of treatment data on-farm
|
Görge, Hannah
|
|
|
5 |
C |
p.
|
artikel
|
| 81 |
Sustainable photovoltaic based protective environment controlled farming technology as economy boosters for agro-sectors
|
Tomar, Anuradha
|
|
|
5 |
C |
p.
|
artikel
|
| 82 |
Tomato leaf disease identification via two–stage transfer learning approach
|
Sanida, Theodora
|
|
|
5 |
C |
p.
|
artikel
|
| 83 |
Towards the characterization of crop and weeds at leaf scale: A large comparison of shape, spatial and textural features
|
Vayssade, Jehan-Antoine
|
|
|
5 |
C |
p.
|
artikel
|
| 84 |
Uncertainty estimation for deep neural networks to improve the assessment of plumage conditions of chickens
|
Lamping, Christian
|
|
|
5 |
C |
p.
|
artikel
|
| 85 |
Understanding microtopography changes in agricultural landscapes through precision assessments of digital surface models by the UAV-RTK-PPK method without ground control points
|
Nakata, Yasutaka
|
|
|
5 |
C |
p.
|
artikel
|
| 86 |
Usage of few-shot learning and meta-learning in agriculture: A literature review
|
Porto, João Vitor de Andrade
|
|
|
5 |
C |
p.
|
artikel
|
| 87 |
Use of computer vision to verify the viability of guavira seeds treated with tetrazolium salt
|
Nucci, Higor Henrique Picoli
|
|
|
5 |
C |
p.
|
artikel
|
| 88 |
Using an open source and resilient technology framework to generate and execute prescription maps for site-specific manure application
|
Bökle, Sebastian
|
|
|
5 |
C |
p.
|
artikel
|
| 89 |
Using machine learning for image-based analysis of sweetpotato root sensory attributes
|
Nakatumba-Nabende, Joyce
|
|
|
5 |
C |
p.
|
artikel
|
| 90 |
Validation of a DEM Model for predicting grain damage in an industrial-scale handling system
|
Chen, Zhengpu
|
|
|
5 |
C |
p.
|
artikel
|
| 91 |
Vision-based normalized canopy area estimation for variable nitrogen application in apple orchards
|
Paudel, Achyut
|
|
|
5 |
C |
p.
|
artikel
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