Ashish Raikwar - Academia.edu (original) (raw)
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Papers by Ashish Raikwar
International Journal of Computer Applications, Mar 31, 2012
This paper presents novel techniques for image retrieval using the clustering features extracted ... more This paper presents novel techniques for image retrieval using the clustering features extracted from images based on Row Mean Clustering, Column Mean clustering, Row Mean DCT Clustering ,Column Mean DCT Clustering, Row Mean Wavelet Clustering and Column Mean Wavelet Clustering. The proposed techniques are compared with well known traditional technique such as Hierarchical Clustering. Hierarchical clustering starts by calculating the Euclidean distance measure for all patterns in data set, which is not required to calculate in proposed techniques. Hence number of clusters used for comparison of proposed techniques is less as compared to existing technique (Hierarchical Clustering). All the CBIR techniques are implemented on a database having 665 images spread across 31 classes. The results of proposed techniques have shown performance improvement (higher precision and Recall) as compared to existing technique at reduced computations.
The Egyptian Journal of Remote Sensing and Space Science, Jun 1, 2015
ABSTRACT Owing to its severe effect on productivity of rain-fed crops and indirect effect on empl... more ABSTRACT Owing to its severe effect on productivity of rain-fed crops and indirect effect on employment as well as per capita income, agricultural drought has become a prime concern worldwide. The occurrence of drought is mainly a climatic phenomenon which cannot be eliminated. However, its effects can be reduced if actual spatio-temporal information related to crop status is available to the decision makers. The present study attempts to assess the efficiency of remote sensing and GIS techniques for monitoring the spatio-temporal extent of agricultural drought. In the present study, NOAA-AVHRR NDVI data were used for monitoring agricultural drought through NDVI based Vegetation Condition Index. VCI was calculated for whole Rajasthan using the long term NDVI images which reveals the occurrence of drought related crop stress during the year 2002. The VCI values of normal (2003) and drought (2002) year were compared with meteorological based Standardized Precipitation Index (SPI), Rainfall Anomaly Index and Yield Anomaly Index and a good agreement was found among them. The correlation coefficient between VCI and yield of major rain-fed crops (r > 0.75) also supports the efficiency of this remote sensing derived index for assessing agricultural drought.
International Journal of Computer Applications, Mar 31, 2012
This paper presents novel techniques for image retrieval using the clustering features extracted ... more This paper presents novel techniques for image retrieval using the clustering features extracted from images based on Row Mean Clustering, Column Mean clustering, Row Mean DCT Clustering ,Column Mean DCT Clustering, Row Mean Wavelet Clustering and Column Mean Wavelet Clustering. The proposed techniques are compared with well known traditional technique such as Hierarchical Clustering. Hierarchical clustering starts by calculating the Euclidean distance measure for all patterns in data set, which is not required to calculate in proposed techniques. Hence number of clusters used for comparison of proposed techniques is less as compared to existing technique (Hierarchical Clustering). All the CBIR techniques are implemented on a database having 665 images spread across 31 classes. The results of proposed techniques have shown performance improvement (higher precision and Recall) as compared to existing technique at reduced computations.
The Egyptian Journal of Remote Sensing and Space Science, Jun 1, 2015
ABSTRACT Owing to its severe effect on productivity of rain-fed crops and indirect effect on empl... more ABSTRACT Owing to its severe effect on productivity of rain-fed crops and indirect effect on employment as well as per capita income, agricultural drought has become a prime concern worldwide. The occurrence of drought is mainly a climatic phenomenon which cannot be eliminated. However, its effects can be reduced if actual spatio-temporal information related to crop status is available to the decision makers. The present study attempts to assess the efficiency of remote sensing and GIS techniques for monitoring the spatio-temporal extent of agricultural drought. In the present study, NOAA-AVHRR NDVI data were used for monitoring agricultural drought through NDVI based Vegetation Condition Index. VCI was calculated for whole Rajasthan using the long term NDVI images which reveals the occurrence of drought related crop stress during the year 2002. The VCI values of normal (2003) and drought (2002) year were compared with meteorological based Standardized Precipitation Index (SPI), Rainfall Anomaly Index and Yield Anomaly Index and a good agreement was found among them. The correlation coefficient between VCI and yield of major rain-fed crops (r > 0.75) also supports the efficiency of this remote sensing derived index for assessing agricultural drought.