Relevant bibliographies by topics / IBM Watson Visual Recognition

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'IBM Watson Visual Recognition'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "IBM Watson Visual Recognition"

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Kumar, Avinash, Pallapothala Tejaswini, Omprakash Nayak, et al. "A Survey on IBM Watson and Its Services." Journal of Physics: Conference Series 2273, no. 1 (2022): 012022. http://dx.doi.org/10.1088/1742-6596/2273/1/012022.

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Abstract Artificial Intelligence (AI) is changing the modern way of lifestyle by helping the person do their jobs in an efficient manner. The AI is currently in its starting phase and from now on it is of great use. IBM Watson is an AI which is used globally by different organizations, institutes and corporations. In this paper we have created a chatbot using IBM Watson Assistance which is helpful in querying about the disease and hospitals related query. This paper also discusses IBM Watson in detail, its applications, its working and case studies on the use of IBM Watson in the field of heal
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Elbouni, Fatima-Zahra, and Aziza EL Ouaazizi. "Birds Images Prediction with Watson Visual Recognition Services from IBM-Cloud and Conventional Neural Network." Advances in Science, Technology and Engineering Systems Journal 7, no. 6 (2022): 181–88. http://dx.doi.org/10.25046/aj070619.

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Bojchuk, Aleksandr A., and Aleksandr G. Galkin. "Application of neural networks for diagnostics of contact network devices: modern approaches and prospects." Innotrans, no. 2 (2024): 10–12. http://dx.doi.org/10.20291/2311-164x-2024-2-10-12.

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The article discusses the prospects of using neural networks for information processing in the field of diagnostics of contact network devices. An overview of software and modern methods using neural networks has been presented, an analysis of software complexes based on fundamentally new methods of data processing obtained during the diagnosis of a contact network has been carried out. For further research, promising software solutions used for analyzing photo and video files have been noted: OpenCV, TensorFlow Object Detection API, YOLO, Amazon Rekognition Video и IBM Watson Visual Recogniti
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Alexander, Kevin, Rayhan Ardiya Dwantara, Raihan Muhammad Naufal, and Derwin Suhartono. "Visual Recognition to Identify Helmet on Motorcycle Rider Using Convolutional Neural Network." CommIT (Communication and Information Technology) Journal 14, no. 2 (2020): 89–94. http://dx.doi.org/10.21512/commit.v14i2.6564.

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The amount of motorcycle accidents is increasing each year. The main reason is that the riders do not wear a helmet. The research aims to minimize the accident by training the machine learning using the IBM Watson Studio. It trains the data about “wearing helmet” and “not wearing helmet”. The used method is Convolutional Neural Network (CNN). About 170 image datasets are used. CNN is conducted on the input image using a kernel or filter. The filter will multiply its values with the overlapping values of the image while also sliding and adding them all to produce a single value for each of them
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Freeman, Daniel, Shaurya Gupta, D. Hudson Smith, et al. "Watson on the Farm: Using Cloud-Based Artificial Intelligence to Identify Early Indicators of Water Stress." Remote Sensing 11, no. 22 (2019): 2645. http://dx.doi.org/10.3390/rs11222645.

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As demand for freshwater increases while supply remains stagnant, the critical need for sustainable water use in agriculture has led the EPA Strategic Plan to call for new technologies that can optimize water allocation in real-time. This work assesses the use of cloud-based artificial intelligence to detect early indicators of water stress across six container-grown ornamental shrub species. Near-infrared images were previously collected with modified Canon and MAPIR Survey II cameras deployed via a small unmanned aircraft system (sUAS) at an altitude of 30 meters. Cropped images of plants in
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Pratik, Roy, Roy Satakshi, Agrawal Rahul, and Sharma Sonal. "Color Based Object Sorting System using Deep Learning." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 5 (2020): 964–68. https://doi.org/10.35940/ijeat.E9896.069520.

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Object sorting is a very common industrial application but at the same time it is a tiresome process as handling so many objects is a menial task which is not so promising in maintaining consistency and thereby arising quality issues. Object sorting, if done manually, is not only time consuming but also it seems to be an uphill task pragmatically. Nowadays amid various technological advancements, industries have become fully automated so an automated sorting system is essentially required to replace this conventional system of manual sorting knowing that this process can be made completely aut
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Tsoi, Kelvin K. F., Felix C. H. Chan, Hoyee W. Hirai, et al. "Data Visualization with IBM Watson Analytics for Global Cancer Trends Comparison from World Health Organization." International Journal of Healthcare Information Systems and Informatics 13, no. 1 (2018): 45–54. http://dx.doi.org/10.4018/ijhisi.2018010104.

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Visual analytics is widely used to explore data patterns and trends. This work leverages cancer data collected by World Health Organization (WHO) across a hundred of cancer registries worldwide. In this study, the authors present a visual analytics platform, IBM Watson Analytics, to explore the patterns of global cancer incidence. They included 26 forms of cancers from eight different geographic regions which are United States, the United Kingdom, Costa Rica, Sweden, Croatia, Japan, Hong Kong and China (Shanghai). An interactive interface was applied to plot a choropleth map to show global can
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Schultz, Benjamin G., Venkata S. Aditya Tarigoppula, Gustavo Noffs, et al. "Automatic speech recognition in neurodegenerative disease." International Journal of Speech Technology 24, no. 3 (2021): 771–79. http://dx.doi.org/10.1007/s10772-021-09836-w.

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AbstractAutomatic speech recognition (ASR) could potentially improve communication by providing transcriptions of speech in real time. ASR is particularly useful for people with progressive disorders that lead to reduced speech intelligibility or difficulties performing motor tasks. ASR services are usually trained on healthy speech and may not be optimized for impaired speech, creating a barrier for accessing augmented assistance devices. We tested the performance of three state-of-the-art ASR platforms on two groups of people with neurodegenerative disease and healthy controls. We further ex
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Ahire, Pritam, Hariharan Achary, and Sourabh Shirke. "Voice-Print Recognition System Using Python And Machine Learning With IBM Watson." IARJSET 8, no. 6 (2021): 16–25. http://dx.doi.org/10.17148/iarjset.2021.8603.

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Choi, Yong-Sik, Jin-Gu Kang, Jong Wha J. Joo, and Jin-Woo Jung. "Real-time Informatized caption enhancement based on speaker pronunciation time database." Multimedia Tools and Applications 79, no. 47-48 (2020): 35667–88. http://dx.doi.org/10.1007/s11042-020-09590-2.

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AbstractIBM Watson is one of the representative tools for speech recognition system which can automatically generate not only speech-to-text information but also speaker ID and timing information, which is called as Informatized Caption. However, if there is some noise in the voice signal to the IBM Watson API, the recognition performance is significantly decreased. It can be easily found in movies with background music and special sound effects. This paper aims to improve the inaccuracy problem of current Informatized Captions in noisy environments. In this paper, a method of modifying incorr
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Dissertations / Theses on the topic "IBM Watson Visual Recognition"

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Vlček, Pavol. "Hlasový dialogový systém ve webovém prohlížeči pro demonstrační účely." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-449168.

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Cieľom práce je navrhnúť a vytvoriť hlasom ovládaného asistenta(voicebota), ktorý bude ľahko nasaditeľný na webovú stránku. Používateľom tak bude poskytnutý moderný spôsob, ako prirodzene komunikovať cez internetový prehliadač. Hlavný dôraz je kladený na synchronizáciu medzi hlasovým asistentom a obsahom na webovej stránke. Synchronizácia je dosiahnutá obojsmerným prenosom hlasu a textových príkazov medzi klientom a serverom. Na to je použitá technológia WebRTC v kombinácií so signalizačným protokolom SIP. Práca sa zaoberá oblasťami ako VoIP telefonovanie, počítačové siete a strojové učenie(pr
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Book chapters on the topic "IBM Watson Visual Recognition"

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Kolluru, S. K., Shreyans Shrimal, and Sudharsan Krishnaswamy. "CognitiveCam: A Visual Question Answering Application." In Applications of Cognitive Computing Systems and IBM Watson. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6418-0_11.

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Biondi, Giulio, Valentina Franzoni, and Valentina Poggioni. "A Deep Learning Semantic Approach to Emotion Recognition Using the IBM Watson Bluemix Alchemy Language." In Computational Science and Its Applications – ICCSA 2017. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62398-6_51.

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Conference papers on the topic "IBM Watson Visual Recognition"

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De Oliveira, Raianny Proença de Camargo, Guilherme Rodrigues Sganderla, Claudio Roberto Marquetto Maurício, and Fabiana Frata Furlan Peres. "Classificação de Imagens de Raio-x de Torax com Reconhecimento Visual da IBM Cloud para Diagnóstico de Pneumonia." In XXXII Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sibgrapi.est.2019.8330.

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A capacidade de aprender por meio de exemplos e formular predições são as principais características do Machine Learning, uma subárea da inteligência artificial. Existem diversos frameworks disponíveis que utilizam Machine Learning para solução dos mais variados tipos de problemas, como para reconhecer e classificar objetos em uma imagem. Utilizando os serviços fornecidos por IBM Watson Visual Recognition que emprega algoritmos de deep learning, uma subárea de Machine learning, um modelo foi criado e aplicado no dataset Chest X-Ray Images for Classification. Os resultados obtidos com o modelo
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De Oliveira, Raianny Proença de Camargo, Valéria Nunes Dos Santos, and Cláudio Roberto Marquetto Maurício. "Reconhecimento de Objetos em Linhas de Distribuição de Energia Utilizando IBM Cloud." In XXXII Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sibgrapi.est.2019.8329.

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O reconhecimento visual de objetos em uma imagem e a habilidade de classificá-los é umas das principais áreas de pesquisa utilizando a inteligência artificial. Atualmente, existem diversos frameworks disponíveis para auxiliar nesta tarefa. IBM Cloud é um desses frameworks no qual oferece um amplo catálogo de ferramentas na área de inteligência artificial, uma delas é a IBM Watson Visual Recognition. Foi criado um modelo através dessa API que utiliza algoritmos de Deep Learning para analisar imagens. O objetivo principal do modelo é o reconhecimento de oito tipos de objetos distintos em linhas
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Bertacchi, Marcello, Ismar Silveira, and Nizam Omar. "A Comparative Analysis of the Evolution of the IBM Watson's Visual Recognition API on Android." In 2017 Workshop of Computer Vision (WVC). IEEE, 2017. http://dx.doi.org/10.1109/wvc.2017.00028.

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Al-Maliky, Rusul S. B. "A Semantic Approach to Emotion Recognition Using IBM Watson Bluemix tone Analyzer and translator Language." In 2019 2nd International Conference on Engineering Technology and its Applications (IICETA). IEEE, 2019. http://dx.doi.org/10.1109/iiceta47481.2019.9012970.

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Niggli, C., H.-C. Pape, and L. Mica. "Validation of IBM-WATSON Health Trauma Pathway explorer, a visual based analytics tool to predict outcomes of poly-trauma patients." In Deutscher Kongress für Orthopädie und Unfallchirurgie. Georg Thieme Verlag KG, 2020. http://dx.doi.org/10.1055/s-0040-1717426.

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Zahra EL Bouni, Fatima, Tareq El Hariri, Chaime Zouitni, Ilham Ben Bahva, Hafida El Aboui, and Aziza El Ouaazizi. "Bird image recognition and classification using Watson visual recognition services from IBMCloud and Conventional Neural Network (CNN)." In 2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE). IEEE, 2021. http://dx.doi.org/10.1109/icecce52056.2021.9514269.

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Bolle, Ruud M., Andrea Califano, John R. Kender, Rick Kjeldsen, and Rakesh Mohan. "Multilevel evidence fusion for the recognition of 3-D objects: an overview of computer vision research at IBM/T.J. Watson." In Fibers '91, Boston, MA, edited by Paul S. Schenker. SPIE, 1991. http://dx.doi.org/10.1117/12.25267.

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