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An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture [article]

Michael A. Beck, Chen-Yi Liu, Christopher P. Bidinosti, Christopher J. Henry, Cara M. Godee, Manisha Ajmani
<span title="2020-06-01">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To tackle this problem, we have developed an embedded robotic system to automatically generate and label large datasets of plant images for ML applications in agriculture.  ...  We now plan to generate much larger datasets of Canadian crop plants and weeds that will be made publicly available in the hope of further enabling ML applications in the agriculture sector.  ...  embedded system (EAGL-I) that can automatically generate and label large datasets of plant images for machine learning applications in agriculture.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.01228v1">arXiv:2006.01228v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ywvj6jqkzjgepfwhxkjlb6clna">fatcat:ywvj6jqkzjgepfwhxkjlb6clna</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200606033629/https://arxiv.org/pdf/2006.01228v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.01228v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture

Michael A. Beck, Chen-Yi Liu, Christopher P. Bidinosti, Christopher J. Henry, Cara M. Godee, Manisha Ajmani, Jeonghwan Gwak
<span title="2020-12-17">2020</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s3gm7274mfe6fcs7e3jterqlri" style="color: black;">PLoS ONE</a> </i> &nbsp;
To tackle this problem, we have developed an embedded robotic system to automatically generate and label large datasets of plant images for ML applications in agriculture.  ...  We now plan to generate much larger datasets of Canadian crop plants and weeds that will be made publicly available in the hope of further enabling ML applications in the agriculture sector.  ...  us to use their magnetic field mapping system as the first prototype of EAGL-I.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0243923">doi:10.1371/journal.pone.0243923</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33332382">pmid:33332382</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/usndjk5lozdbhmeplz2ktzuqva">fatcat:usndjk5lozdbhmeplz2ktzuqva</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210225194921/https://storage.googleapis.com/plos-corpus-prod/10.1371/journal.pone.0243923/1/pone.0243923.pdf?X-Goog-Algorithm=GOOG4-RSA-SHA256&amp;X-Goog-Credential=wombat-sa%40plos-prod.iam.gserviceaccount.com%2F20210225%2Fauto%2Fstorage%2Fgoog4_request&amp;X-Goog-Date=20210225T194921Z&amp;X-Goog-Expires=3600&amp;X-Goog-SignedHeaders=host&amp;X-Goog-Signature=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" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/40/b8/40b84a90adaadce8bfb0b257065c0008cf594c5b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0243923"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> plos.org </button> </a>

Challenges and Opportunities in Machine-Augmented Plant Stress Phenotyping

Arti Singh, Sarah Jones, Baskar Ganapathysubramanian, Soumik Sarkar, Daren Mueller, Kulbir Sandhu, Koushik Nagasubramanian
<span title="2020-08-20">2020</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s7wj3rwofngddnaxae7vb54u3e" style="color: black;">Trends in Plant Science</a> </i> &nbsp;
We propose an overarching strategy for utilizing ML techniques that methodically enables the application of plant stress phenotyping at multiple scales across different types of stresses, program goals  ...  The growing capabilities of machine learning (ML) methods in conjunction with image-based phenotyping can extract new insights from curated, annotated, and high-dimensional datasets across varied crops  ...  In the past decade, significant advances in image processing and machine learning (ML; see Glossary) algorithms have been made to handle image-based stress datasets for automated data analysis and application  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.tplants.2020.07.010">doi:10.1016/j.tplants.2020.07.010</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32830044">pmid:32830044</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/soplocjs5jfpnipyryxpk7jmcq">fatcat:soplocjs5jfpnipyryxpk7jmcq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201103205739/https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1436&amp;context=me_pubs" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0a/7e/0a7e55b267e2d692542737ed582f6f071a2d9e38.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.tplants.2020.07.010"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>

Identification of Tobacco Crop based on Machine Learning for a Precision Agricultural Sprayer

Muhammad Tufail, Javaid Iqbal, Mohsin Islam Tiwana, Muhammad Shahab Alam, Zubair Ahmad Khan, Muhammad Tahir Khan
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
This paper presents a machine-learning based crop/weed detection system for a tractor-mounted boom sprayer that could perform site-specific spraying on tobacco crop in fields.  ...  INDEX TERMS Crop and weed detection, machine-learning, precision agriculture.  ...  This makes the developed proposed solution (SVM with hand-engineered Haralick, Hu, and color feature) suitable to be embedded in an agricultural precision sprayer.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3056577">doi:10.1109/access.2021.3056577</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u7li4ejw45cflienbwcuockozi">fatcat:u7li4ejw45cflienbwcuockozi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210718013001/https://ieeexplore.ieee.org/ielx7/6287639/9312710/09344674.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d0/11/d011259cea1678c8cf65f0da00e189461dc79823.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3056577"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

GREEN HOUSE AUTOMATION VIA GPRS

RAMPRABU .J, KAMINI .D
<span title="">2015</span> <i title="Institute for Project Management Pvt. Ltd"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wf4zauwmhfgtxa3una6bns6vsq" style="color: black;">International journal of computer and communication technology</a> </i> &nbsp;
Appropriate climatic condition are necessary for plant growth ,improve crop yields, efficient use of water and to control the diseased plants.  ...  To protect the plants from the adverse climatic conditions such as wind, cold, precepitation, excessive radiation, extreme temperature, insects and diseases.The need for greenhouse automation arises.  ...  Support vector machines are an innovative approach to constructing learning machines that minimize the generalization error.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.47893/ijcct.2015.1314">doi:10.47893/ijcct.2015.1314</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/l2rfmgqpebd37p7sv6gbmwchee">fatcat:l2rfmgqpebd37p7sv6gbmwchee</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201029125746/https://www.interscience.in/cgi/viewcontent.cgi?article=1314&amp;context=ijcct" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cc/a0/cca09671fd35ccc489d885790df71eb9dc17c4cc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.47893/ijcct.2015.1314"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Opportunities for Robotic Systems and Automation in Cotton Production

Edward Barnes, Gaylon Morgan, Kater Hake, Jon Devine, Ryan Kurtz, Gregory Ibendahl, Ajay Sharda, Glen Rains, John Snider, Joe Mari Maja, J. Alex Thomasson, Yuzhen Lu (+10 others)
<span title="2021-05-28">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lfjvgonolffjfotecgw4jyubxe" style="color: black;">AgriEngineering</a> </i> &nbsp;
The growing availability of autonomous machines in agriculture indicates that there are opportunities to increase automation in cotton production.  ...  Automation continues to play a greater role in agricultural production with commercial systems now available for machine vision identification of weeds and other pests, autonomous weed control, and robotic  ...  [74] used a stereoscopic camera, machine vision processing, a deep learning network model (YOLOv3), and an embedded computer to manage computation of the images to identify cotton bolls in the field  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/agriengineering3020023">doi:10.3390/agriengineering3020023</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pvcifsr5c5hzthehqnts6fda6y">fatcat:pvcifsr5c5hzthehqnts6fda6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210608235014/https://res.mdpi.com/d_attachment/agriengineering/agriengineering-03-00023/article_deploy/agriengineering-03-00023-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/07/8e/078ea779c45ea109b6f9477a0f2e5b696124dc9b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/agriengineering3020023"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

sCrop: A Internet-of-Agro-Things (IoAT) Enabled Solar Powered Smart Device for Automatic Plant Disease Prediction [article]

Venkanna Udutalapally and Saraju P. Mohanty and Vishal Pallagani and Vedant Khandelwal
<span title="2020-05-09">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The proposed deep learning framework for plant disease prediction has achieved an accuracy of 99.2% testing accuracy.  ...  The deployment of the proposed system is demonstrated in a real-time environment using a microcontroller, solar sensor nodes with a camera module, and an mobile application for the farmers visualization  ...  In this article, we propose the novel concept of Internet-of-Agro-Things (IoAT) to make next generation Smart Agriculture with an integrated machine learning (ML) model for automatic plant disease prediction  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.06342v1">arXiv:2005.06342v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lw6dhv5ribg5plpyxb4nrq464y">fatcat:lw6dhv5ribg5plpyxb4nrq464y</a> </span>
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Disruptive Technologies in Smart Farming: An Expanded View with Sentiment Analysis

Sargam Yadav, Abhishek Kaushik, Mahak Sharma, Shubham Sharma
<span title="2022-05-12">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lfjvgonolffjfotecgw4jyubxe" style="color: black;">AgriEngineering</a> </i> &nbsp;
Application of these predictive and innovative tools in agriculture is crucial for handling unprecedented conditions such as climate change and the increasing global population.  ...  ) such as machine learning and big data.  ...  A brief description of these labels is given in Table 8 , along with the total number of comments for each label, and an example of the label from the dataset.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/agriengineering4020029">doi:10.3390/agriengineering4020029</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mv2tmloy3rcvbek64ezddfu3qy">fatcat:mv2tmloy3rcvbek64ezddfu3qy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220514203054/https://mdpi-res.com/d_attachment/agriengineering/agriengineering-04-00029/article_deploy/agriengineering-04-00029.pdf?version=1652354689" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d9/e3/d9e34a9bfd15ee3a7b1557263b4812e5712ad6c7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/agriengineering4020029"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Internet of Things and Machine Learning Applications for Smart Precision Agriculture [chapter]

R. Sivakumar, B. Prabadevi, G. Velvizhi, S. Muthuraja, S. Kathiravan, M. Biswajita, A. Madhumathi
<span title="2021-05-07">2021</span> <i title="IntechOpen"> Ubiquitous Computing [Working Title] </i> &nbsp;
The evolutions of Machine Learning (ML) and the Internet of Things (IoT) have supported researchers to implement this automation in agriculture to support farmers.  ...  Besides, it elucidates the problems, specific potential solutions, and future directions for the agriculture sector using Machine Learning and the Internet of things.  ...  It adopts the techniques like in-row treatment to spray fertiliser for each plant separately, sensor-equipped drones to track the weed, automated sensing of fertiliser details from the barcode label for  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/intechopen.97679">doi:10.5772/intechopen.97679</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2stbj72a3bf67bgs72swxtglf4">fatcat:2stbj72a3bf67bgs72swxtglf4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210520051932/https://api.intechopen.com/chapter/pdf-download/76652.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c3/12/c312ed6062ab90cc4cd35f7e48085f5f5c8695f7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/intechopen.97679"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Learning Aided System for Agriculture Monitoring Designed Using Image Processing and IoT-CNN

Kandarpa Kumar Sarma, Kunal Kingkar Das, Vikash Mishra, Samadrita Bhuiya, Dmitrii Kaplun
<span title="">2022</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Out of several AI tools, CNN proves to be effective in providing automated decision support for classifying the plant leaf disease types through a cloud server that can be accessed using an app.  ...  The proposed system has a sensor pack that provides continuous data capture of temperature records, air and soil moisture and a camera for obtaining near-infrared (NIR) images of the plant leaves for use  ...  The most substantial results are in the fields of digital signal and image processing, embedded systems, neural networks, and machine learning.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2022.3167061">doi:10.1109/access.2022.3167061</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h443yknvmbeszo4viygi3bo3zu">fatcat:h443yknvmbeszo4viygi3bo3zu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220506015621/https://ieeexplore.ieee.org/ielx7/6287639/9668973/09756536.pdf?tp=&amp;arnumber=9756536&amp;isnumber=9668973&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/13/ee/13eec09a2d5aa49b7a9bb4980feba562f7b0697a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2022.3167061"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Agriculture Robots using Deep Learning

<span title="2020-03-30">2020</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3sfifsouvjgadp4gfj54u3z2ku" style="color: black;">International journal of recent technology and engineering</a> </i> &nbsp;
Agricultural researchers often use software systems without an appropriate analysis of the ideas and mechanisms of a technique.  ...  Agriculture is very important to the continuation of mankind, which maintains a driving factor for many world economies, especially in stunted and emerging countries.  ...  Intelligence was viewed as an additional enabler and a major technical critique to fostering the intellectual capital worth of all precision agriculture.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijrte.f7823.038620">doi:10.35940/ijrte.f7823.038620</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ubc3g6x2jjfa7ajbl5cfah247e">fatcat:ubc3g6x2jjfa7ajbl5cfah247e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200506220058/https://www.ijrte.org/wp-content/uploads/papers/v8i6/F7823038620.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2b/0e/2b0e80936970030e619043120c9a76ebed150c88.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijrte.f7823.038620"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions

Andreas Holzinger, Anna Saranti, Alessa Angerschmid, Carl Orge Retzlaff, Andreas Gronauer, Vladimir Pejakovic, Francisco Medel-Jimenez, Theresa Krexner, Christoph Gollob, Karl Stampfer
<span title="2022-04-15">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
, the workhorse of AI, statistical machine learning (ML).  ...  This goal will also require an agile, human-centered design approach for three generations (G). G1: Enabling easily realizable applications through immediate deployment of existing technology.  ...  Through the head-mounted display camera that observes the plants, images of the plant leaves are captured in real time and sent to the cloud server for analysis, which also provides a lot of room for detecting  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s22083043">doi:10.3390/s22083043</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35459028">pmid:35459028</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC9029836/">pmcid:PMC9029836</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/73bojrnysrcnzfkem4eomrupqy">fatcat:73bojrnysrcnzfkem4eomrupqy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220507142548/https://mdpi-res.com/d_attachment/sensors/sensors-22-03043/article_deploy/sensors-22-03043-v2.pdf?version=1650246225" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/31/5a/315acb4dece97c44e54e5ada981f68ed4e780d90.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s22083043"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9029836" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives

Asheesh Kumar Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Arti Singh
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s7wj3rwofngddnaxae7vb54u3e" style="color: black;">Trends in Plant Science</a> </i> &nbsp;
Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile tool to assimilate large amounts of heterogeneous data and provide reliable predictions of complex and uncertain  ...  We review recent work where DL principles have been utilized for digital image-based plant stress phenotyping.  ...  Soybean Association (A.S., A.K.S.); Monsanto Chair in Soybean Breeding (A.K.S.); R F Baker Center for Plant Breeding (A.K.S.), United States Department of Agriculture -NIFA project to all authors; and  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.tplants.2018.07.004">doi:10.1016/j.tplants.2018.07.004</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30104148">pmid:30104148</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/32sw4te2izenpj4vmyhztdcgqa">fatcat:32sw4te2izenpj4vmyhztdcgqa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190502001902/https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1590&amp;context=agron_pubs" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/06/7a/067aa61f39d2489cb1efb29877144bd2e2a4b540.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.tplants.2018.07.004"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Identification of fruit tree pests with deep learning on embedded drone to achieve accurate pesticide spraying

Ching-Ju Chen, Ya-Yu Huang, Yuan-Shuo Li, Ying-Cheng Chen, Chuan-Yu Chang, Yueh-Min Huang
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Novel applications for edge intelligence are applied in this study to establish an intelligent pest recognition system to manage this pest problem.  ...  Apart from planning the optimized spraying of pesticide for the spraying drone, the TX2 embedded platform also transmits the position and generation of pests to the cloud to record and analyze the growth  ...  Therefore, we have collected many samples in this work. After labeling the images, we used an Imgaug library for image augmentation in the machine learning experiments for data augmentation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3056082">doi:10.1109/access.2021.3056082</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tuaj5cyu6zhtpobw4lhksq7r7a">fatcat:tuaj5cyu6zhtpobw4lhksq7r7a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717232347/https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343827.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e2/04/e204bc0fceadca18c56d4688f69440ac7e3866a9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3056082"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Deep Learning Application in Plant Stress Imaging: A Review

Zongmei Gao, Zhongwei Luo, Wen Zhang, Zhenzhen Lv, Yanlei Xu
<span title="2020-07-14">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lfjvgonolffjfotecgw4jyubxe" style="color: black;">AgriEngineering</a> </i> &nbsp;
In this paper, we reviewed the latest deep learning approaches pertinent to the image analysis of crop stress diagnosis.  ...  Developments of advanced sensing and machine learning techniques trigger revolutions for precision agriculture based on deep learning and big data.  ...  The second one is automated data labeling, which utilizes machine learning to label portions of the provided data automatically.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/agriengineering2030029">doi:10.3390/agriengineering2030029</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ehqowfrcdrddlgpr63rtkkfwxm">fatcat:ehqowfrcdrddlgpr63rtkkfwxm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200807104203/https://res.mdpi.com/d_attachment/agriengineering/agriengineering-02-00029/article_deploy/agriengineering-02-00029.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/84/79/847946cb931c24c628b6e16ddbaa2fa1fa3ab9ee.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/agriengineering2030029"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>
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