%0 Journal Article %1 noauthororeditor %A Manjunath, Sneha N Thota Santosh C R %D 2018 %J International Journal of Trend in Scientific Research and Development %K Agriculture classifier image machine networks neural processing support vector %N 4 %P 163-168 %T A Comparative Study on Agricultural Crop Disease Detection Systems %U http://www.ijtsrd.com/computer-science/other/12870/a-comparative-study-on-agricultural-crop-disease-detection-systems/sneha-n %V 2 %X Agriculture is a widely practiced profession. During cultivation of crops taking sufficient care of the crops is very necessary. A variety of fungi and bacterial diseases affect the crop in growth. Early diagnosis and detection of crop diseases leads to an increased yield of crops. For this reason, a lot of researches have been going on worldwide to develop systems that are efficient and feasible in agricultural crop disease detection. Thus, it has been an interesting area of research. So, we carry out a thorough study of around 13 papers and various other articles, covering disease detection systems on rice, wheat, paddy, cucumber and grapes. Also, we try to present a comparative study based on the criteria Methodology. Sneha N | Thota Santosh | C R ManjunathÄ Comparative Study on Agricultural Crop Disease Detection Systems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12870.pdf http://www.ijtsrd.com/computer-science/other/12870/a-comparative-study-on-agricultural-crop-disease-detection-systems/sneha-n

@article{noauthororeditor, abstract = {Agriculture is a widely practiced profession. During cultivation of crops taking sufficient care of the crops is very necessary. A variety of fungi and bacterial diseases affect the crop in growth. Early diagnosis and detection of crop diseases leads to an increased yield of crops. For this reason, a lot of researches have been going on worldwide to develop systems that are efficient and feasible in agricultural crop disease detection. Thus, it has been an interesting area of research. So, we carry out a thorough study of around 13 papers and various other articles, covering disease detection systems on rice, wheat, paddy, cucumber and grapes. Also, we try to present a comparative study based on the criteria Methodology. Sneha N | Thota Santosh | C R Manjunath"A Comparative Study on Agricultural Crop Disease Detection Systems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12870.pdf http://www.ijtsrd.com/computer-science/other/12870/a-comparative-study-on-agricultural-crop-disease-detection-systems/sneha-n }, added-at = {2018-09-05T12:47:14.000+0200}, author = {Manjunath, Sneha N Thota Santosh C R}, biburl = {https://www.bibsonomy.org/bibtex/26992c02589a2bcff11071f95690e6245/ijtsrd}, interhash = {411bf389956584beea23ad5ad339d473}, intrahash = {6992c02589a2bcff11071f95690e6245}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Agriculture classifier image machine networks neural processing support vector}, language = {English}, month = {June}, number = 4, pages = {163-168}, timestamp = {2018-10-02T11:01:27.000+0200}, title = {A Comparative Study on Agricultural Crop Disease Detection Systems }, url = {http://www.ijtsrd.com/computer-science/other/12870/a-comparative-study-on-agricultural-crop-disease-detection-systems/sneha-n}, volume = 2, year = 2018 }