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Titlebook: Recent Trends in Image Processing and Pattern Recognition; First International K.C. Santosh,Mallikarjun Hangarge,Atul Negi Conference proc

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樓主: Racket
51#
發(fā)表于 2025-3-30 08:28:06 | 只看該作者
Complex and Composite Graphical Symbol Recognition and Retrieval: A Quick Reviewnition problem, three different approaches: statistical, structural and syntactic are taken into account. It includes fundamental concepts or techniques and research standpoints or directions derived by a real-world application.
52#
發(fā)表于 2025-3-30 12:33:30 | 只看該作者
53#
發(fā)表于 2025-3-30 20:34:42 | 只看該作者
54#
發(fā)表于 2025-3-30 21:47:03 | 只看該作者
1865-0929 efully reviewed and selected from 99 submissions. The papers are organized in topical sections on?document analysis;?pattern analysis and machine learning; image analysis;?biomedical image analysis;?biometrics..978-981-10-4858-6978-981-10-4859-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
55#
發(fā)表于 2025-3-31 04:49:51 | 只看該作者
56#
發(fā)表于 2025-3-31 06:50:54 | 只看該作者
57#
發(fā)表于 2025-3-31 10:35:39 | 只看該作者
58#
發(fā)表于 2025-3-31 16:25:07 | 只看該作者
An Approach for Logo Detection and Retrieval in Documentses such as conference certificates, degree certificates, attendance certificates, etc. Further, to study the efficiency of the proposed method we have compared the obtained results with the results provided by five human experts and the results are more encouraging.
59#
發(fā)表于 2025-3-31 21:01:19 | 只看該作者
Word Retrieval from Kannada Document Images Using HOG and Morphological Features word, based on it, the relevance of the word is estimated by generating distance ranks. Then correctly matched words are selected at threshold 98%. The experimental results confirm the efficiency of our proposed method in terms of the average precision rate 91.23%, and average recall rate 84.78% as well as average F-measure 89.47%.
60#
發(fā)表于 2025-3-31 22:41:31 | 只看該作者
Comparative Study of Handwritten Marathi Characters Recognition Based on KNN and SVM Classifierientation and Euler number. The modified k-nearest neighbor (KNN) and SVM algorithm with five fold validation has been used for result preparation. The comparative accuracy of proposed methods are recorded. In this experiment modified SVM obtained high accuracy as compared with KNN classifier.
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