Academic literature on the topic 'Kannada Authors'

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Journal articles on the topic "Kannada Authors"

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Ravi, P., C. Naveena, and Y. H. Sharath Kumar. "Deep Learning in Historical Kannada Document." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 4111–15. http://dx.doi.org/10.1166/jctn.2020.9028.

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Kannada is one of the famous ancient languages of the India and the official language of the State of Karnataka, which has a very large heritage. The digital analysis of these historical Kannada documents will provide us information about the culture and traditions that were practiced. Retrieving such information from paper documents, palm leaves or from stone carvings will enhance our knowledge. Investigating Historical document isn’t straight advance procedure because of low quality, differentiation, contrast and covering of characters. In this analysis, the authors propose a novel Scale invariant Feature Transform (SIFT) with deep learning classifier to recognize Historical kannada characters. To begin with, the character is divided utilizing Connected Component Analysis and later the Different SIFT Features are detached. At long last, form a powerful convolutional neural system classifier to recognize the Historical kannada archives. Proposed tale schemes during the preprocessing stage to guarantee strong, precise and constant grouping. They assess their strategy all alone datasets their characterization results surpass 97% on all datasets, which are superior to the cutting edge in this space.
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GOSAVI, KUMAR VINOD CHHOTUPURI, NILESH APPASO MADHAV, VIKAS BHAT KHANDIGE, and ARUN NIVRUTTI CHANDORE. "Rediscovery of little-known-monotypic genus Karnataka P.K.Mukh. & Constance (Apiaceae)." Phytotaxa 601, no. 1 (July 5, 2023): 97–102. http://dx.doi.org/10.11646/phytotaxa.601.1.8.

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Karnataka (Apiaceae) is a monotypic genus rediscovered after it’s type collection around 175 years from Mudbidri area of Dakshina Kannada (South Canara) district, Karnataka. Detailed morphological description, identity notes and photoplates have been provided based on fresh material collected by authors.
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Jha, Paridhi, Vikas Kumar Jha, Bharati Sharma, Ajeya Jha, Kerstin Erlandsson, and Malin Bogren. "Cultural adaptation and psychometric evaluation of Childbirth Experience Questionnaire 2 in Karnataka state, India." PLOS ONE 18, no. 11 (November 28, 2023): e0291591. http://dx.doi.org/10.1371/journal.pone.0291591.

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Background Women’s birthing experience is a sensitive indicator of the quality of childbirth care and can impact the physical and mental health of both women and their neonates. Negligible evidence exists on Indian women’s birth experiences and–to the best of authors’ knowledge–no questionnaire has been tested in India for measuring women’s birthing experiences. This study aimed to test the construct validity and reliability of the Kannada-translated Revised Childbirth Experience Questionnaire. Methodology A cross-sectional survey was carried out among postnatal women (n = 251, up to six months postpartum, with a live healthy neonate) who had given birth at a public or private health facility using the Kannada-translated CEQ2 in two districts of Karnataka. Data were collected at participants’ homes after seeking written informed consent. Model fit was determined by Confirmatory Factor Analyses. Results The 4-factor model of the CEQ2 showed good fit after deletion of one item (item 8, subcategory “participation”) with CMIN = 1.33; SRMR = 0.04; GFI = 0.92, CFI = 0.98, TLI = 0.99, RMSEA = 0.037 and p value 0.002). The Cronbach alpha values were acceptable for the four subscales (0.92, 0.93, 0.97, 0.91) as well as for the overall 21-item scale (0.84). Conclusions The Kannada-translated CEQ2 is a reliable tool to measure the childbirth experiences among Kannada-speaking women and can serve as a reliable ongoing evaluation of women’s birth experiences.
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Rudregowda, Shashidhar, Sudarshan Patil Kulkarni, Gururaj H L, Vinayakumar Ravi, and Moez Krichen. "Visual Speech Recognition for Kannada Language Using VGG16 Convolutional Neural Network." Acoustics 5, no. 1 (March 16, 2023): 343–53. http://dx.doi.org/10.3390/acoustics5010020.

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Visual speech recognition (VSR) is a method of reading speech by noticing the lip actions of the narrators. Visual speech significantly depends on the visual features derived from the image sequences. Visual speech recognition is a stimulating process that poses various challenging tasks to human machine-based procedures. VSR methods clarify the tasks by using machine learning. Visual speech helps people who are hearing impaired, laryngeal patients, and are in a noisy environment. In this research, authors developed our dataset for the Kannada Language. The dataset contained five words, which are Avanu, Bagge, Bari, Guruthu, Helida, and these words are randomly chosen. The average duration of each video is 1 s to 1.2 s. The machine learning method is used for feature extraction and classification. Here, authors applied VGG16 Convolution Neural Network for our custom dataset, and relu activation function is used to get an accuracy of 91.90% and the recommended system confirms the effectiveness of the system. The proposed output is compared with HCNN, ResNet-LSTM, Bi-LSTM, and GLCM-ANN, and evidenced the effectiveness of the recommended system.
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Parathra Sreedharanpillai, Ambili, Biku Abraham, and Arun Kotapuzakal Varghese. "Optically processed Kannada script realization with Siamese neural network model." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (March 1, 2024): 1112. http://dx.doi.org/10.11591/ijai.v13.i1.pp1112-1118.

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<p><span>Optical character recognition (OCR) is a technology that allows computers to recognize and extract text from images or scanned documents. It is commonly used to convert printed or handwritten text into machine-readable format. This Study presents an OCR system on Kannada Characters based on siamese neural network (SNN). Here the SNN, a Deep neural network which comprises of two identical convolutional neural network (CNN) compare the script and ranks based on the dissimilarity. When lesser dissimilarity score is identified, prediction is done as character match. In this work the authors use 5 classes of Kannada characters which were initially preprocessed using grey scaling and convert it to pgm format. This is directly input into the Deep convolutional network which is learnt from matching and non-matching image between the CNN with contrastive loss function in Siamese architecture. The Proposed OCR system uses very less time and gives more accurate results as compared to the regular CNN. The model can become a powerful tool for identification, particularly in situations where there is a high degree of variation in writing styles or limited training data is available.</span></p>
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Singh, Rajeev, and P. Diwakar. "Gregarious flowering of Strobilanthes callosus Nees in Western Ghats." Indian Journal of Forestry 30, no. 4 (December 1, 2007): 553–55. http://dx.doi.org/10.54207/bsmps1000-2007-3j264x.

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Strobilanthes callosus Nees is endemic to India and flowers once in its life cycle. In Peninsular India, it is reported in bloom after 7 years. During a botanical tour to Anshi National Park, Mookambika Wildlife Sanctuary and Kudremukh National Park, the authors reported this species in bloom in Pune, Satara, Kolhapur (Maharashtra), Belgaum, Dharwad, Koppal, Udupi, Mangalore, Shimoga, Davanagere, Uttara Kannada and Haveri Districts (Karnataka). From Koppal, Udupi, Mangalore, Davanagere and Haveri Districts of Karnataka, this species hitherto not reported. A complete citation, short description and notes are given. This documentation is essential to ascertain periodicity in blooming for various species of Strobilanthes.
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Reddy, P. Deepak. "Multilingual Speech to Text using Deep Learning based on MFCC Features." Machine Learning and Applications: An International Journal 9, no. 02 (June 30, 2022): 21–30. http://dx.doi.org/10.5121/mlaij.2022.9202.

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The proposed methodology presented in the paper deals with solving the problem of multilingual speech recognition. Current text and speech recognition and translation methods have a very low accuracy in translating sentences which contain a mixture of two or more different languages. The paper proposes a novel approach to tackling this problem and highlights some of the drawbacks of current recognition and translation methods. The proposed approach deals with recognition of audio queries which contain a mixture of words in two different languages - Kannada and English. The novelty in the approach presented, is the use of a next Word Prediction model in combination with a Deep Learning speech recognition model to accurately recognise and convert the input audio query to text. Another method proposed to solve the problem of multilingual speech recognition and translation is the use of cosine similarity between the audio features of words for fast and accurate recognition. The dataset used for training and testing the models was generated manually by the authors as there was no pre-existing audio and text dataset which contained sentences in a mixture of both Kannada and English. The DL speech recognition model in combination with the Word Prediction model gives an accuracy of 71% when tested on the in-house multilingual dataset. This method outperforms other existing translation and recognition solutions for the same test set. Multilingual translation and recognition is an important problem to tackle as there is a tendency for people to speak in a mixture of languages. By solving this problem, the barrier of language and communication can be lifted and thus can help people connect better and more comfortably with each other.
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Higdon, Jeff W. "Second reply to the comment by Romero and Kannada on “Genetic analysis of 16th-century whale bones prompts a revision of the impact of Basque whaling on right and bowhead whales in the western North Atlantic”Appears in Can. J. Zool. 84(7): 1059–1065." Canadian Journal of Zoology 86, no. 1 (January 2008): 76–79. http://dx.doi.org/10.1139/z07-118.

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The comments by A. Romero and S. Kannada (2006. Can. J. Zool. 84: 1059–1065) provide a brief summary of North Atlantic whaling history as a critique of T. Rastogi et al. (2004. Can. J. Zool. 82: 1647–1654) . However, they fall far short of providing an accurate review of whaling history in this region. The authors present a number of factual errors, misuse several key sources, and make significant omissions, ultimately defeating the purpose of providing information to biologists, managers, and historians. In this comment I highlight the mistakes in their representation of the history of North Atlantic whaling for bowhead whales ( Balaena mysticetus L., 1758). There are unacceptable errors for most nations covered, and for American whaling in particular. The authors assert that over 30 000 bowhead whales were landed by Yankee whalers in the North Atlantic when the vast majority were in fact taken on the Pacific grounds. Although a summary of whaling history is an admirable goal and of potential value, it is unfortunate that the authors missed such an opportunity by failing to adequately research this topic, failing to include important citations, and by including sources that do not provide the information indicated. Providing a whaling summary with such errors and omissions only adds further confusion to an already confusing theme.
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Gayathri, Karukayil Sivadas, and Shivani Tiwari. "Authors' responses to the comments on “Adaptation and Validation of Parental Behavioral Scale for Children with Autism Spectrum Disorders to Kannada”." Indian Journal of Psychological Medicine 41, no. 5 (September 2019): 499–500. http://dx.doi.org/10.4103/ijpsym.ijpsym_357_19.

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Kadam, Dipali M. "Diasporic consciousness in contemporary Indian women’s fiction in English: at a glance." RUDN Journal of Studies in Literature and Journalism 27, no. 3 (October 12, 2022): 532–40. http://dx.doi.org/10.22363/2312-9220-2022-27-3-532-540.

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Diasporic literature is a pivotal term in literature that includes the literary works of the authors who are the outsiders for their native country but their work is deeply rooted in homeland by reflecting native culture, background, displacement and so on. Indian women’s literary work is at the forefront of diasporic literature. The advent of Indian women novelists on the literary horizon is an important development in the Indian English literature. These women writers have also contributed to other genres, such as drama, poetry and short stories, not only in English but also in regional languages like Hindi, Marathi, Bengali, Punjabi, Tamil, Kannada and so on. Some modern women writers flourish their writing in the form of fables as a literary genre in an impressive way to focus on the specific themes. In last two decades, Indian women’s writing in English is blossomed, both published in India and abroad. The present paper is the review of diasporic consciousness in select works of contemporary Indian women novelists. It focuses on the attempt to highlight the quest for identity of those women who played a crucial role in defining themselves through their literary work in diasporic background.
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Books on the topic "Kannada Authors"

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Ḍi, Kurtakōṭi Ke. Kannaḍa sāhitya saṅgāti. Kamalāpura, Hampi: Prasārāṅga, Kannaḍa Viśvavidyālaya, 1995.

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Niṅgōji, Mañjunātha. Kannaḍa sāhitigaḷa paricaya. Gadaga: Vijēt Prakāśana, 2006.

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Gokak, Vinayak Krishna. Pravāsa sāhitya. Beṅgaḷūru: Aibiec Prakāśana, 1988.

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Ke, En. Nenapellā kallu sakkare. Hubbaḷḷi: Sāhitya Prakāśana, 2003.

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Jōśi, Ji Ḍi. Kannaḍada pōṣakaru. Dhāravāḍa: Karnāṭaka Vidyāvardhaka Saṅgha, 2005.

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Bhaṭṭa, Seḍiyāpu Kṛṣṇa. Īśvara saṅkalpa, athavā, Daivalīle mattu ajjana kathegaḷu. Uḍupi: Rāṣṭrakavi Gōvinda Pai Saṃśōdhana Kēndra, 1996.

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Aḍiga, Kurāḍi Sītārāma. Jīvana rēkhe. Beṅgaḷūru: Sumukha Prakāśana, 2007.

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Mahāliṅgaśeṭṭi, Pārvatamma. Heṇṇina dr̥ṣṭiyalli ī śatamāna. Beṅgaḷūru: Ai. Bi. Ec. Prakāśana, 1998.

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Prahlād, Ḍi Vi. Bage tereda bānu: Sandarśanagaḷu. Beṅgaḷūru: Sañcaya, 1996.

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Kulakarṇi, Vi Bi. Saṃśōdhaka Ḍā. Śaṃ. Bā. Jōśi. Hubbaḷḷi: Burli Bindu Mādhava Smāraka Pratiṣṭhāna, 1996.

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Book chapters on the topic "Kannada Authors"

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"About the Author." In Kannagi Through the Ages. Bloomsbury India, 2022. http://dx.doi.org/10.5040/9789394701182.0010.

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Mukankusi, Laurence, Jared Keengwe, Yao Amewokunu, and Assion Lawson-Body. "Relationships between Wireless Technology Investment and Organizational Performance." In Encyclopedia of Multimedia Technology and Networking, Second Edition, 1206–14. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-014-1.ch164.

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Information technology (IT) investments are justified based on average improvement in performance (Peacock & Tanniru, 2005). Firms rely on those investments (Demirhan, Jacob, & Raghunathan, 2002; Duh, Chow, & Chen, 2006; Tuten, 2003) because executives believe that investments in wireless technologies help boost company performance. In this regard, the benefits from wireless technology applications depend on the extent to which they are congruent with the firm’s performance (Duh et al., 2006). But, some IS researchers argue that competitors may easily duplicate investments in IT resources by purchasing the same hardware, software, and network, and hence resources necessarily do not provide sustained performance (Santhanam & Hartono, 2003). The use of wireless communications and computing is growing quickly (Kim & Steinfield, 2004; Leung & Cheung, 2004; Yang, Chatterjee, & Chan, 2004). The future of wireless technology may also bring more devices that can operate using the many different standards and it may be possible that a global standard is accepted, such as the expected plans for the 3G technology UMTS. The wireless beyond 3G (B3G) systems or the so called composite radio environments (CRE) (or even 4G systems) possess multiple features that allow employees to collaborate with each other and provide diverse access alternatives (Kouis, Domestichas, Koundourakis, & Theologou, 2007). But issues of risk and uncertainty due to technical, organizational, and environmental factors continue to hinder executive efforts to produce meaningful evaluation of investment in wireless technology (Smith, Kulatilaka, & Venkatramen, 2002). Despite the use of investment appraisal techniques, executives are often forced to rely on instinct when finalizing wireless investment decisions. A key problem with evaluation techniques that emerges is their treatment of uncertainty and their failure to account for the fact that outside of a decision to reject an investment outright, firms may have an option to defer an investment until a later period (Tallon, Kauffman, Lucas, Whinston, & Zhu, 2002). In addition, many authors believe that if firms can combine the appropriate investment strategies to create a unique wireless technology capability, superior firm performance can be the result. Utilization of wireless devices and being “connected” without wires is inevitable (Gebauer, Shaw, & Gribbins, 2004; Jarvenpaa, Lang, Reiner, Yoko, & Virpi, 2003). Market researchers predict that by the end of 2005, there will be almost 500 million users of wireless devices, generating more than $200 billion in revenues (Chang & Kannan, 2002; Xin, 2004). And by 2006, the global mobile commerce (m-commerce) market will be worth $230 billion (Chang & Kannan, 2002). Such predictions indicate the importance that is attached to wireless technologies as a way of supporting business activities. Evaluating investments in wireless technology and understanding which technology makes the “best fit” for a company or organization performance is difficult because of the numerous technologies and the costs, risks, and potential benefits associated with each technology.
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