Understanding cartoon emotion using integrated deep neural network on large dataset

Jain, Nikita; Gupta, Vishal; Shubham, Shubham; Madan, Agam; Chaudhary, Ankit; Santosh, K. C.

doi:10.1007/s00521-021-06003-9

Cited by 27 publications

(7 citation statements)

References 34 publications

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“…Several techniques have been applied to solve the vanishing gradient problem. RNN (Jain et al , 2021) uses its internal memory to process temporal patterns of different lengths. This enables RNNs to produce patterns for text analysis. Gated recurrent units (GRUs) is a type of RNN used for addressing the issue of short-term memory.…”

Section: Methodsmentioning

confidence: 99%

A deep neural network-based approach for fake news detection in regional language

Katariya

Gupta

Arora

et al. 2022

IJWIS

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Purpose The current natural language processing algorithms are still lacking in judgment criteria, and these approaches often require deep knowledge of political or social contexts. Seeing the damage done by the spreading of fake news in various sectors have attracted the attention of several low-level regional communities. However, such methods are widely developed for English language and low-resource languages remain unfocused. This study aims to provide analysis of Hindi fake news and develop a referral system with advanced techniques to identify fake news in Hindi. Design/methodology/approach The technique deployed in this model uses bidirectional long short-term memory (B-LSTM) as compared with other models like naïve bayes, logistic regression, random forest, support vector machine, decision tree classifier, kth nearest neighbor, gated recurrent unit and long short-term models. Findings The deep learning model such as B-LSTM yields an accuracy of 95.01%. Originality/value This study anticipates that this model will be a beneficial resource for building technologies to prevent the spreading of fake news and contribute to research with low resource languages.

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Section: Methodsmentioning

confidence: 99%

A deep neural network-based approach for fake news detection in regional language

Katariya

Gupta

Arora

et al. 2022

IJWIS

Self Cite

View full text Add to dashboard Cite

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“…Later they were implemented in a separate environment with the same characteristics: i. e. a 4-core ARM-Cortex processor and 4 GB of RAM, in an environment without a graphics card. Different programming languages were used to implement each model, the first model used C++, the second model used the Darknet platform for training and Python for evaluation, and the third used Python with TensorFlow library [22][23][24].…”

Section: F Recall Precision Precision Recall Tp Precision Recall Tp F...mentioning

confidence: 99%

Identification of weeds in fields based on computer vision technology

Kaldarova,

Аkanova,

Nazyrova

et al. 2023

EEJET

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The problem of multiple zones in computer vision, including pattern recognition in the agricultural sector, occupies a special place in the field of artificial intelligence in the modern aspect. The object of the study is the recognition of weeds based on deep learning and computer vision. The subject of the study is the effective use of neural network models in training, involving classification and processing using datasets of plants and weeds. The relevance of the study lies in the demand of the modern world in the use of new information technologies in industrial agriculture, which contributes to improving the efficiency of agro-industrial complexes. The interest of private agricultural enterprises and the state is caused by an increase in the yield of agricultural products. To recognize weeds, machine learning methods, in particular neural networks, were used. The process of weed recognition is described using the Mark model, as a result of processing 1,562 pictures, segmented images are obtained. Due to the annual increase in weeds on the territory of Kazakhstan and in the course of solving these problems, a new plant recognition code was developed and written in the scanner software module. The scanner, in turn, provides automatic detection of weeds. Based on the results of a trained neural network based on the MaskRCNN neural network model written in the scanner software module meeting new time standards, the automated plant scanning and recognition system was improved. The weed was recognized in an average of 0.2 seconds with an accuracy of 89 %, while the additional human factor was completely removed. The use of new technology helps to control weeds and contributes to solving the problem of controlling them

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“…Big Data Analytics could also be used for studies related to the spread of pandemics, the efficacy of covid treatment [ 18 , 79 ], or psychology and psychiatry studies, e.g. emotion recognition [ 35 ].…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

The use of Big Data Analytics in healthcare

2022

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The introduction of Big Data Analytics (BDA) in healthcare will allow to use new technologies both in treatment of patients and health management. The paper aims at analyzing the possibilities of using Big Data Analytics in healthcare. The research is based on a critical analysis of the literature, as well as the presentation of selected results of direct research on the use of Big Data Analytics in medical facilities. The direct research was carried out based on research questionnaire and conducted on a sample of 217 medical facilities in Poland. Literature studies have shown that the use of Big Data Analytics can bring many benefits to medical facilities, while direct research has shown that medical facilities in Poland are moving towards data-based healthcare because they use structured and unstructured data, reach for analytics in the administrative, business and clinical area. The research positively confirmed that medical facilities are working on both structural data and unstructured data. The following kinds and sources of data can be distinguished: from databases, transaction data, unstructured content of emails and documents, data from devices and sensors. However, the use of data from social media is lower as in their activity they reach for analytics, not only in the administrative and business but also in the clinical area. It clearly shows that the decisions made in medical facilities are highly data-driven. The results of the study confirm what has been analyzed in the literature that medical facilities are moving towards data-based healthcare, together with its benefits.

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Understanding cartoon emotion using integrated deep neural network on large dataset

Cited by 27 publications

References 34 publications

A deep neural network-based approach for fake news detection in regional language

A deep neural network-based approach for fake news detection in regional language

Identification of weeds in fields based on computer vision technology

The use of Big Data Analytics in healthcare

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