Titlebook: Computational Intelligence in Pattern Recognition; Proceedings of CIPR Asit Kumar Das,Janmenjoy Nayak,Danilo Pelusi Conference proceedings

ungainly

Search for Planets by Spectroscopic Methodsnt, we demonstrate that the accuracy is improved by the CNNs over the conventional SVM and other classification methods. The result of the proposed method has good accuracy in the classification and it is close to 98% for the four classes of 1200 fruit images, indicating that the proposed method could be used in agro-based applications.

火光在摇曳

抵制

cuticle

Strategies in Clinical Hematologyose. A 6-headed Machine Learning tf–idf Model has been made and trained separately, yielding a Mean Validation Accuracy of 98.08% and Absolute Validation Accuracy of 91.64%. Such an Automated System should be deployed for enhancing the healthy online conversation.

Madrigal

Current Problems of Iron Overload,lemented and tested on real fingerprint images. The experimental results show the efficiency and accuracy of the method. A comparative study is also provided between the proposed method and other relevant techniques which proves the efficacy of the method.

CLEFT

anthropologist

milligram

A Novel Enhancement and Segmentation of Color Retinal Image Based on Fuzzy Measure and Fuzzy Integrch is used for enhancement and fuzzy integral is applied for segmentation. The proposed algorithm can accomplish excellent contrast and a segment of an image object that endows feasibility in diagnosis from retinal image.

串通

Detection and Identification of Parasite Eggs from Microscopic Images of Fecal Samples,from the segmented images. For classification, Artificial Neural Network (ANN) and Multi-class Support Vector Machine (MC-SVM) are used. The experimental result shows about 95% and 93% accuracy rate in identifying Ascaris eggs using MC-SVM and ANN, respectively.

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