Deep Learning

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[3]  Andreas Kamilaris,et al.  Deep learning in agriculture: A survey , 2018, Comput. Electron. Agric..

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[5]  Alsayed Algergawy,et al.  A Deep Learning-based Approach for Banana Leaf Diseases Classification , 2017, BTW.

[6]  Aditya Khamparia,et al.  SVM and PCA Based Learning Feature Classification Approaches for E-Learning System , 2018, Int. J. Web Based Learn. Teach. Technol..

[7]  Jian Zhang,et al.  CNN Transfer Learning for Automatic Image-Based Classification of Crop Disease , 2018, IGTA.

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[9]  Wenzhun Huang,et al.  Three-channel convolutional neural networks for vegetable leaf disease recognition , 2019, Cognitive Systems Research.

[10]  Yoshua Bengio,et al.  Convolutional networks for images, speech, and time series , 1998 .

[11]  Rasmus Nyholm Jørgensen,et al.  RoboWeedSupport - Detection of weed locations in leaf occluded cereal crops using a fully convolutional neural network , 2017 .

[12]  Rasmus Nyholm Jørgensen,et al.  RoboWeedSupport - Presentation of a cloud based system bridging the gap between in-field weed inspections and decision support systems , 2017 .

[13]  Aditya Khamparia,et al.  A novel method of case representation and retrieval in CBR for e-learning , 2015, Education and Information Technologies.

[14]  Juan C. Caicedo,et al.  Fine-tuning Deep Convolutional Networks for Plant Recognition , 2015, CLEF.

[15]  Li Yujian,et al.  A comparative study of fine-tuning deep learning models for plant disease identification , 2019, Comput. Electron. Agric..

[16]  Niko Sünderhauf,et al.  Evaluation of Features for Leaf Classification in Challenging Conditions , 2015, 2015 IEEE Winter Conference on Applications of Computer Vision.

[17]  Muhammad Intizar Ali,et al.  Agri-IoT: A semantic framework for Internet of Things-enabled smart farming applications , 2016, 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT).

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[19]  Andreas Kamilaris,et al.  A review on the practice of big data analysis in agriculture , 2017, Comput. Electron. Agric..

[20]  Marcel Salathé,et al.  Using Deep Learning for Image-Based Plant Disease Detection , 2016, Front. Plant Sci..

[21]  Hang Zhang,et al.  Deep Texture Manifold for Ground Terrain Recognition , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[22]  Olarik Surinta,et al.  Comparing Local Descriptors and Bags of Visual Words to Deep Convolutional Neural Networks for Plant Recognition , 2017, ICPRAM.

[23]  M. Wackernagel,et al.  Shrink and share: humanity's present and future Ecological Footprint , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[24]  Jayme G. A. Barbedo,et al.  Impact of dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification , 2018, Comput. Electron. Agric..

[25]  Tristan Perez,et al.  DeepFruits: A Fruit Detection System Using Deep Neural Networks , 2016, Sensors.

[26]  David Hughes,et al.  Deep Learning for Image-Based Cassava Disease Detection , 2017, Front. Plant Sci..

[27]  Maryam Rahnemoonfar,et al.  Deep Count: Fruit Counting Based on Deep Simulated Learning , 2017, Sensors.

[28]  Mustafa Teke,et al.  A short survey of hyperspectral remote sensing applications in agriculture , 2013, 2013 6th International Conference on Recent Advances in Space Technologies (RAST).

[29]  Avinash C. Tyagi,et al.  Towards a Second Green Revolution , 2016 .

[30]  Artzai Picón,et al.  Automatic plant disease diagnosis using mobile capture devices, applied on a wheat use case , 2017, Comput. Electron. Agric..

[31]  C. Weaver,et al.  White Vegetables: A Forgotten Source of Nutrients: Purdue Roundtable Executive Summary , 2013, Advances in nutrition.

[32]  Artzai Picón,et al.  Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild , 2019, Comput. Electron. Agric..

[33]  Yang Yang,et al.  Remote Sensing of Irrigated Agriculture: Opportunities and Challenges , 2010, Remote. Sens..