An Intelligent VegeCare Tool for Corn Disease Classification

Due to the decrease of the agricultural population, agriculture has widely applied to machine learning and deep learning. In this paper, we present the classification performance of the proposed VegeCare tool for corn disease classification. We classify the major leaf diseases of the corn crop. The dataset includes four classes: gray leaf spot, common rust, health and northern leaf blight. From this evaluation, we found that our proposed VegeCare tool has a good performance.

[1]  Channamallikarjuna Mattihalli,et al.  Plant leaf diseases detection and auto-medicine , 2018, Internet Things.

[2]  Yi Li,et al.  Convolutional Neural Networks for Document Image Classification , 2014, 2014 22nd International Conference on Pattern Recognition.

[3]  Demis Hassabis,et al.  Mastering the game of Go with deep neural networks and tree search , 2016, Nature.

[4]  Shane Legg,et al.  Human-level control through deep reinforcement learning , 2015, Nature.

[5]  Yee Whye Teh,et al.  A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.

[6]  Adem Tuncer,et al.  Plant Leaf Disease Detection and Classification Based on CNN with LVQ Algorithm , 2018, 2018 3rd International Conference on Computer Science and Engineering (UBMK).

[7]  Luc Martens,et al.  System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops , 2020, IEEE Access.

[8]  Debashis De,et al.  Internet of Things (IoT) for Smart Precision Agriculture and Farming in Rural Areas , 2018, IEEE Internet of Things Journal.

[9]  Chee Yen Leow,et al.  An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges , 2018, IEEE Internet of Things Journal.

[10]  Anderson Rocha,et al.  Automatic Classifier Fusion for Produce Recognition , 2012, 2012 25th SIBGRAPI Conference on Graphics, Patterns and Images.

[11]  Honglak Lee,et al.  Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.

[12]  Manos M. Tentzeris,et al.  A uW Backscatter-Morse-Leaf Sensor for Low-Power Agricultural Wireless Sensor Networks , 2018, IEEE Sensors Journal.

[13]  Leonard Barolli,et al.  Performance Evaluation of VegeCare Tool for Potato Disease Classification , 2020, NBiS.

[14]  Marc'Aurelio Ranzato,et al.  Building high-level features using large scale unsupervised learning , 2011, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[15]  Andrea Berton,et al.  IEEE 802.15.4 Air-Ground UAV Communications in Smart Farming Scenarios , 2018, IEEE Communications Letters.

[16]  Demis Hassabis,et al.  Mastering the game of Go without human knowledge , 2017, Nature.

[17]  Marcel Salathé,et al.  An open access repository of images on plant health to enable the development of mobile disease diagnostics through machine learning and crowdsourcing , 2015, ArXiv.

[18]  R. GeethaRamani,et al.  Identification of plant leaf diseases using a nine-layer deep convolutional neural network , 2019, Comput. Electr. Eng..