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Titlebook: Intelligent Systems Design and Applications; 18th International C Ajith Abraham,Aswani Kumar Cherukuri,Niketa Gandhi Conference proceedings

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發(fā)表于 2025-3-25 07:02:59 | 只看該作者
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發(fā)表于 2025-3-25 17:38:34 | 只看該作者
A Semi-local Method for Image Retrieval,g histograms of global features found inside each bloc..The results obtained by the proposed method are illustrated through some experiments on Wang and Holidays Dataset. The obtained Results show the simplicity and efficiency of our proposal.
25#
發(fā)表于 2025-3-25 20:08:37 | 只看該作者
Differential Evolution Trained Fuzzy Cognitive Map: An Application to Modeling Efficiency in Bankinof training namely (i) sequential and (ii) batch modes. We compared the DE trained FCM models with the conventional Hebbian training in both modes. We employed Mean Absolute Percentage Error (MAPE) as an error measure while predicting the efficiency from Return on Assets (ROA), Return on Equity (ROE
26#
發(fā)表于 2025-3-26 01:56:53 | 只看該作者
Novel Authentication System for Personal and Domestic Network Systems Using Image Feature Compariso have been developed since the last few decades in digital security to secure and encrypt data. As much as these techniques are versatile and robust, authentication systems remain the weakest link in any given cyber-physical system. Human intervention does not necessarily make a system as robust as
27#
發(fā)表于 2025-3-26 04:22:03 | 只看該作者
Detecting Helmet of Bike Riders in Outdoor Video Sequences for Road Traffic Accidental Avoidance,Due to deeply regretted reports from the loss of manpower and economy, accidental avoidance becomes a hot challenging research topic. In this paper, we consider specifically the accidents that happen due to bike rider’s involvement. Focusing on detecting helmet test, we proposed a computer vision ba
28#
發(fā)表于 2025-3-26 09:07:49 | 只看該作者
29#
發(fā)表于 2025-3-26 15:36:42 | 只看該作者
30#
發(fā)表于 2025-3-26 17:29:22 | 只看該作者
Bidirectional LSTM Joint Model for Intent Classification and Named Entity Recognition in Natural Laion (NER) tasks. Both the models are approached as a classification task. This paper discuss the comparison of single models and joint models in the respective tasks, a data augmentation algorithm and how the joint model framework helped in learning a poor performing NER model in by adding learned w
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