A method for counting and classifying aphids using computer vision

[1]  V. Tzin,et al.  Cereal aphids differently affect benzoxazinoid levels in durum wheat , 2018, PloS one.

[2]  Lars Monrad Hansen.  Establishing control threshold for bird cherry-oat aphid (Rhopalosiphum padi L.) in spring barley (Hordeum vulgare L.) by aphid-days. , 2000 .

[3]  F. Fabre,et al.  The conflicting relationships between aphids and men: a review of aphid damage and control strategies. , 2010, Comptes rendus biologies.

[4]  Sergey Ioffe,et al.  Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Ray E. Sheriff,et al.  Convolution neural network in precision agriculture for plant image recognition and classification , 2017, 2017 Seventh International Conference on Innovative Computing Technology (INTECH).

[6]  Heather D. Couture,et al.  Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype , 2018, npj Breast Cancer.

[7]  Anuprita Mande,et al.  Detection of Fruit Ripeness Using Image Processing , 2018 .

[8]  R. Rabbinge,et al.  Cereal aphid populations: biology, simulation and prediction. , 1982 .

[9]  Li Shen,et al.  Deep Learning to Improve Breast Cancer Detection on Screening Mammography , 2017, Scientific Reports.

[10]  Emily F Hamilton,et al.  Comparison of 5 experts and computer analysis in rule-based fetal heart rate interpretation. , 2010, American journal of obstetrics and gynecology.

[11]  Richard Szeliski,et al.  Computer Vision - Algorithms and Applications , 2011, Texts in Computer Science.

[12]  Jacob Goldberger,et al.  Obstacle detection in a greenhouse environment using the Kinect sensor , 2015, Comput. Electron. Agric..

[13]  A. A. Fanaroff.  Comparison of 5 experts and computer analysis in rule-based fetal heart rate interpretation , 2011 .

[14]  P. Pereira,et al.  Population Growth and Damage Caused by Rhopalosiphum padi (L.) (Hemiptera, Aphididae) on Different Cultivars and Phenological Stages of Wheat , 2013, Neotropical Entomology.

[15]  S. Nadeem,et al.  Role of Wheat Varieties and Insecticide Applications against Aphids for Better Wheat Crop Harvest , 2017 .

[16]  Herbert Schildt.  Java: The Complete Reference , 1996 .

[17]  Jayme Garcia Arnal Barbedo,et al.  Using digital image processing for counting whiteflies on soybean leaves , 2014 .

[18]  N. Razavian,et al.  Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning , 2018, Nature Medicine.

[19]  Margaret Kosmala,et al.  Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning , 2017, Proceedings of the National Academy of Sciences.

[20]  Tae-Soo Chon,et al.  Automatic identification and counting of small size pests in greenhouse conditions with low computational cost , 2015, Ecol. Informatics.

[21]  Gary R. Bradski,et al.  Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library , 2016 .

[22]  D. Sathish,et al.  Identification and counting of pests using extended region grow algorithm , 2015, 2015 2nd International Conference on Electronics and Communication Systems (ICECS).

[23]  Wei Wu,et al.  Detection of aphids in wheat fields using a computer vision technique , 2016 .

[24]  Nicola J. Ferrier,et al.  Repetitive motion analysis: segmentation and event classification , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Sreekala G. Bajwa,et al.  Identification and Counting of Soybean Aphids from Digital Images Using Shape Classification , 2017 .

[26]  P. Tato,et al.  Automatic counting of immunocytochemically stained cells , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).