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ADMRF: Elucidation of deep feature extraction and adaptive deep Markov random fields with improved heuristic algorithm for speech emotion recognition
On considering Human–Computer Interaction, the recognition of emotion over speech is developed from the niche phase into the most essential...
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A real-time human bone fracture detection and classification from multi-modal images using deep learning technique
Human bone is an essential structure that allows the body to move. It is a common observation in contemporary society that bone fractures occur...
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CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement
Image color difference (CD) measurement, a crucial concept in color science and imaging technology, aims to quantify the perceived difference between...
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An expert method for defining the adaptation conditions of irrigated crops with the ecosystem of Northwestern China
The uncertain impacts of climate changes on the crop water requirements disarrange the on-farm balance of water supply and demand, thus here needs to...
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Research on satellite link allocation algorithm for Earth-Moon space information network
With ongoing advancements in space exploration and communication technology, the realization of an Earth-Moon space information network is gradually...
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Learning to sculpt neural cityscapes
We introduce a system that learns to sculpt 3D models of massive urban environments. The majority of humans live their lives in urban environments,...
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Picture fuzzy filters on residuated lattices
Filters play an important role in studying fuzzy logics. From a logical point of view, filters correspond to sets of provable formulae. In this...
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Optimization of the different controller parameters via OBL approaches based artificial ecosystem optimization involving fitness distance balance guiding mechanism for efficient motor speed regulation of DC motor
This study proposes a new optimization approach, which is called as artificial ecosystem optimization algorithm with fitness-distance balance guiding...
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Intelligent Personality Assessment and Verification from Handwriting using Machine Learning
It is possible to tell a lot about a person just by looking at their handwriting. The way someone writes might tell you a lot about who, they are as...
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k-filters and k-\(\{^*\}\)-congruences of core regular double Stone algebras
In this paper, we investigate various elegant filters and congruences of the class of core regular double Stone algebras (briefly CRD -Stone...
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Integrating metaheuristics and artificial intelligence for healthcare: basics, challenging and future directions
Accurate and rapid disease detection is necessary to manage health problems early. Rapid increases in data amount and dimensionality caused...
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Deep learning framework for stock price prediction using long short-term memory
Forecasting stock prices is always considered as complicated process due to the dynamic and noisy characteristics of stock data influenced by...
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Prediction of servo industry development in China by an optimized reverse Hausdorff fractional discrete grey power model
In order to accurately predict the development of the servo industry in China, this study proposes a Hausdorff fractional reverse accumulated grey...
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Hierarchical contrastive representation for zero shot learning
Zero-shot learning aims to identify unseen (novel) objects, using only labeled samples from seen (base) classes. Existing methods usually learn...
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Achieving accurate and balanced regional electric vehicle charging load forecasting with a dynamic road network: a case study of Lanzhou City
AbstractSpatial and temporal predictions of electric vehicle (EV) charging loads provide a basis for further research on synergistic operation of...
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Anomaly analytics in data-driven machine learning applications
Machine learning is used widely to create a range of prediction or classification models. The quality of the machine learning (ML) models depends not...
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Progress on half a century of process modelling research in steelmaking: a review
Process modelling in steelmaking started from mid-sixties and witnessed rapid growth and wide spread applications during the last fifty years or so....
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Exploring Brazilian Teachers’ Perceptions and a priori Needs to Design Smart Classrooms
Smart classrooms offer innovative opportunities to enhance teaching and learning. However, most existing research in this field predominantly focuses...
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DGNN-MN: Dynamic Graph Neural Network via memory regenerate and neighbor propagation
Dynamic Graph Neural Network (DGNN) models have been widely used for modelling, prediction and recommendation tasks in domains such as e-commerce and...
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DMFVAE: miRNA-disease associations prediction based on deep matrix factorization method with variational autoencoder
MicroRNAs (miRNAs) are closely related to numerous complex human diseases, therefore, exploring miRNA-disease associations (MDAs) can help people...