Titlebook: International Symposium on Intelligent Informatics; Proceedings of ISI 2 Sabu M. Thampi,Jayanta Mukhopadhyay,Kuan-Ching Li Conference proce

faultfinder

DCLL—A Deep Network for Possible Real-Time Decoding of Imagined Wordsre employs a sliding window with overlap for data augmentation (DA) and common spatial pattern (CSP) in order to derive the features. The dimensionality of features is reduced using linear discriminant analysis (LDA). Long short-term memory (LSTM) along with majority voting is used as the classifier

biosphere

Towards Frugal Artificial Intelligence: Exploring Neural Network Pruning and Binarizationdea of Frugal Artificial Intelligence has been put forward. While there are many ways to make AI frugal, this contribution focuses on two of them, namely neural network pruning and binarization. Experimental results obtained for the CIFAR-100 and CalTech-256 datasets are presented and analysed. Seve

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Practical Implications of Dequantization on Machine Learning Algorithms: A Surveyh gains have not been realized in practice. The quantum inspired algorithms can theoretically achieve significant speed up based on sampling assumptions and have thus far failed to outperform the existing classical ML models in practical applications. The speedup of quantum machine learning (QML) al

syncope

Encoder–Decoder Network with Guided Transmission Map: Robustness and Applicabilityrpose are examined in this paper. The EDN-GTM utilizes the transmission map extracted by dark channel prior approach as an additional input channel of a novel U-Net-based generative network to achieve an improved dehazing performance. The EDN-GTM has shown a very favorable performance compared with

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Development of NN-Based Ball Bearing Fault Diagnosis Techniquesprimary source of failure in any machine. So, monitoring the health of bearings becomes important to prevent any catastrophic machine failures and avoid unpredicted machine downtime. This paper uses open-source data from the Case Western Reserve University (CWRU) to monitor the health of bearings. F

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Gradual Search and Fixed Grouping Scheme Based Variant of Genetic Algorithm for Large Scale Global Oalgorithms, including Genetic Algorithm (GA), face this problem. The article first identifies schema deception, domino convergence with genetic drift and nonseparability among the variables as the reasons for LSGO. Towards LSGO solution, the article progresses the cooperative coevolution approach, w

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