A review of recent sensing technologies to detect invertebrates on crops
暂无分享,去创建一个
[1] D. K. Weaver,et al. Acoustic system for insect detection in plant stems: Comparisons of Cephus cinctus in wheat and Metamasius callizona in bromeliads , 2004 .
[2] Sumio Kawano,et al. Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes , 2013 .
[3] Jung-Kwon Oh,et al. Feasibility of ultrasonic spectral analysis for detecting insect damage in wooden cultural heritage , 2013, Journal of Wood Science.
[4] Peng Yan-jun. Application of Watershed Algorithm in Image of Food Insects , 2007 .
[5] F. Kurtulmuş,et al. Detection of dead entomopathogenic nematodes in microscope images using computer vision , 2014 .
[6] Jafar Massah,et al. Performance evaluation of a machine vision system for insect pests identification of field crops using artificial neural networks , 2013 .
[7] Eamonn J. Keogh,et al. Towards Automatic Classification on Flying Insects Using Inexpensive Sensors , 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.
[8] Shintaroh Ohashi,et al. Nondestructive detection of internal insect infestation in jujubes using visible and near-infrared spectroscopy , 2011 .
[9] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[10] Richard Szeliski,et al. Computer Vision - Algorithms and Applications , 2011, Texts in Computer Science.
[11] J. Chahl. Range and egomotion estimation from compound photodetector arrays with parallel optical axis using optical flow techniques. , 2014, Applied optics.
[12] Noel D.G. White,et al. Detection techniques for stored-product insects in grain , 2007 .
[13] Marten Postma,et al. Mechanisms of Light Adaptation in Drosophila Photoreceptors , 2005, Current Biology.
[14] Bernard Tomasini,et al. Acoustic detection and automatic identification of insect stages activity in grain bulks by noise spectra processing through classification algorithms. , 2006 .
[15] M. Zorović,et al. Laser vibrometry as a diagnostic tool for detecting wood-boring beetle larvae , 2014, Journal of Pest Science.
[16] Varsha,et al. Genetically modified crops : tools for insect pest and weed control in cotton and canola , 2008 .
[17] I. Cuthill,et al. Visual pigments, cone oil droplets and ocular media in four species of estrildid finch , 2000, Journal of Comparative Physiology A.
[18] Thomas G. Dietterich,et al. Segmentation of touching insects based on optical flow and NCuts , 2013 .
[19] Matthijs C. Dorst. Distinctive Image Features from Scale-Invariant Keypoints , 2011 .
[20] Eibe Frank,et al. Logistic Model Trees , 2003, ECML.
[21] Noel D.G. White,et al. Identification of wheat kernels damaged by the red flour beetle using X-ray images , 2004 .
[22] Feng Yang,et al. Mobile smart device-based vegetable disease and insect pest recognition method , 2013, Intell. Autom. Soft Comput..
[23] Chris Saunders,et al. Development of a Proximal Machine Vision System for off-Season Weed Mapping in Broadacre no-tillage Fallows , 2013, J. Comput. Sci..
[24] Enrique Moltó,et al. Automatic sex detection of individuals of Ceratitis capitata by means of computer vision in a biofactory. , 2009, Pest management science.
[25] Nancy A. Schellhorn,et al. The real cost of pesticides in Australia's food boom , 2013 .
[26] Wei Guo,et al. Visual Tracking Using an Insect Vision Embedded Particle Filter , 2015 .
[27] Noel D.G. White,et al. Identification of insect-damaged wheat kernels using short-wave near-infrared hyperspectral and digital colour imaging , 2010 .
[28] Francis Fleurat-Lessard,et al. Experimental study of acoustic equipment for real-time insect detection in grain bins - Assessment of their potential for infestation risk prediction during long term storage periods. , 2009 .
[29] Danilo Monarca,et al. Nondestructive detection of insect infested chestnuts based on NIR spectroscopy , 2014 .
[30] Sang-Joon Lee,et al. IMPROVEMENT OF WOOD CT IMAGES BY CONSIDERATION OF THE SKEWING OF ULTRASOUND CAUSED BY GROWTH RING ANGLE , 2008 .
[31] W. Demtröder. Applications of Laser Spectroscopy , 2015 .
[32] H. P. Zeigier,et al. Vision, brain, and behavior in birds. , 1994 .
[33] Noel D.G. White,et al. Assessment of soft X-ray imaging for detection of fungal infection in wheat , 2009 .
[34] A. Weeks,et al. The current status of pesticide resistance in Australian populations of the redlegged earth mite (Halotydeus destructor). , 2012, Pest management science.
[35] Dario Floreano,et al. Miniature curved artificial compound eyes , 2013, Proceedings of the National Academy of Sciences.
[36] Jacky Emmerton,et al. Wavelength discrimination in the ‘visible’ and ultraviolet spectrum by pigeons , 1980, Journal of comparative physiology.
[37] David C. Slaughter,et al. Robust hyperspectral vision-based classification for multi-season weed mapping , 2012 .
[38] Konstantinos Fysarakis,et al. Insect Biometrics: Optoacoustic Signal Processing and Its Applications to Remote Monitoring of McPhail Type Traps , 2015, PloS one.
[39] Rodrigo Castañeda-Miranda,et al. Machine vision algorithm for whiteflies (Bemisia tabaci Genn.) scouting under greenhouse environment , 2009 .
[40] D. Jayas,et al. Classification of Bulk Samples of Cereal Grains using Machine Vision , 1999 .
[41] J. Buerano,et al. Microphone system optimization for free fall impact acoustic method in detection of rice kernel damage , 2012 .
[42] Bernhard P. Wrobel,et al. Multiple View Geometry in Computer Vision , 2001 .
[43] R. Mankin,et al. Detection of Anoplophora glabripennis (Coleoptera: Cerambycidae) Larvae in Different Host Trees and Tissues by Automated Analyses of Sound-Impulse Frequency and Temporal Patterns , 2008, Journal of economic entomology.
[44] Richard Beare. A locally constrained watershed transform , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Mark A. O'Neill,et al. Automated identification of live moths (Macrolepidoptera) using digital automated identification System (DAISY) , 2004 .
[46] Noel D.G. White,et al. Comparison of soft X-rays and NIR spectroscopy to detect insect infestations in grain , 2005 .
[47] Berthold K. P. Horn,et al. Determining Optical Flow , 1981, Other Conferences.
[48] J. Yack,et al. Vibration detection and discrimination in the masked birch caterpillar (Drepana arcuata) , 2012, Journal of Comparative Physiology A.
[49] Chris Saunders,et al. DEVELOPMENT OF A MACHINE VISION SYSTEM FOR WEED DETECTION DURING BOTH OF OFF-SEASON AND IN-SEASON IN BROADACRE NO-TILLAGE CROPPING LANDS , 2014 .
[50] D. Stavenga,et al. Simple exponential functions describing the absorbance bands of visual pigment spectra , 1993, Vision Research.
[51] Jacob Goldberger,et al. Automatic acoustic detection of the red palm weevil , 2008 .
[52] C. Hoy. Integrated Pest Management: Pesticide resistance management , 2008 .
[53] S. Mcgregor. Insect pollination of cultivated crop plants. , 1976 .
[54] Amy Roda,et al. Perspective and Promise: a Century of Insect Acoustic Detection and Monitoring , 2011 .
[55] P. E. Sankaranarayanan,et al. Wireless implementation of mems accelerometer to detect red palm weevil on palms , 2013, 2013 International Conference on Advanced Electronic Systems (ICAES).
[56] I. Schwab. Vision, Brain, and Behavior in Birds , 1994 .
[57] Shih-Chii Liu,et al. Motion Detection Chips for Robotic Platforms , 2010, Flying Insects and Robots.
[58] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[59] A Feasibility Study Using Simplified near Infrared Imaging to Detect Fruit Fly Larvae in Intact Fruit , 2011 .
[60] N. Hart. The Visual Ecology of Avian Photoreceptors , 2001, Progress in Retinal and Eye Research.
[61] Valda Rondelli,et al. Automatic trap for moth detection in integrated pest management , 2011 .
[62] R. L. Crocker,et al. Eavesdropping on Insects Hidden in Soil and Interior Structures of Plants , 2000, Journal of economic entomology.
[63] Floyd E. Dowell,et al. Comparison of Three near Infrared Spectrophotometers for Infestation Detection in Wild Blueberries Using Multivariate Calibration Models , 2009 .
[64] Georg Siegmund,et al. Targeting the Limits of Laser Doppler Vibrometry , 2005 .
[65] V. Chelladurai,et al. Detection of Callosobruchus maculatus (F.) infestation in soybean using soft X-ray and NIR hyperspectral imaging techniques , 2014 .
[66] Thomas G. Dietterich,et al. Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).
[67] Noel D.G. White,et al. Detection of sprouted wheat kernels using soft X-ray image analysis , 2007 .
[68] John Chambers,et al. Detection of external and internal insect infestation in wheat by near-infrared reflectance spectroscopy , 1996 .
[69] Bo Peng,et al. A System for Detection and Recognition of Pests in Stored-Grain Based on Video Analysis , 2010, CCTA.
[70] Jun Lv,et al. An Insect Imaging System to Automate Rice Light-Trap Pest Identification , 2012 .
[71] Daniel E. Guyer,et al. Comparison of transmittance and reflectance to detect insect infestation in Montmorency tart cherry , 2008 .
[72] Sumio Kawano,et al. Applying near Infrared Spectroscopy to the Detection of Fruit Fly Eggs and Larvae in Intact Fruit , 2010 .
[73] Vincent Martin,et al. A cognitive vision approach to early pest detection in greenhouse crops , 2008 .
[74] Rodrigo Castañeda-Miranda,et al. Original paper: Scale invariant feature approach for insect monitoring , 2011 .
[75] A. Enis Çetin,et al. Feasibility of impact-acoustic emissions for detection of damaged wheat kernels , 2007, Digit. Signal Process..
[76] Panmanas Sirisomboon,et al. Study on non-destructive evaluation methods for defect pods for green soybean processing by near-infrared spectroscopy. , 2009 .
[77] Luc Vincent,et al. Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..
[78] Shintaroh Ohashi,et al. Detection of external insect infestations in jujube fruit using hyperspectral reflectance imaging , 2011 .