Sign language recognition, an essential interface between the hearing and deaf-mute communities, faces challenges with high false positive rates and computational costs, even with the use of advanced deep learning techniques. Our proposed solution is...
Fatigue of miners is caused by intensive workloads, long working hours, and shift-work schedules. It is one of the major factors increasing the risk of safety problems and work mistakes. Examining the detection of miner fatigue is important because i...
International journal of molecular sciences
Nov 9, 2023
Artificial intelligence (AI) has gained significant traction in the field of drug discovery, with deep learning (DL) algorithms playing a crucial role in predicting protein-ligand binding affinities. Despite advancements in neural network architectur...
Real-world retinal optical coherence tomography (OCT) scans are available in abundance in primary and secondary eye care centres. They contain a wealth of information to be analyzed in retrospective studies. The associated electronic health records a...
Brain-like artificial intelligence (AI) will become the main form and important platform in future computing. It will play an important and unique role in simulating brain functions, efficiently implementing AI algorithms, and improving computing pow...
Comprehensive analysis of tissue cell type composition using microscopic techniques has primarily been confined to ex vivo approaches. Here, we introduce NuCLear (Nucleus-instructed tissue composition using deep learning), an approach combining in vi...
Drug-drug interactions (DDIs) are a critical component of drug safety surveillance. Laboratory studies aimed at detecting DDIs are typically difficult, expensive, and time-consuming; therefore, developing in-silico methods is critical. Machine learni...
Dimension reduction is one of the most sought-after strategies to cope with high-dimensional ever-expanding datasets. To address this, a novel deep-learning architecture has been designed with multiple deconstruction and single reconstruction layers ...
The selection of relevant genes plays a vital role in classifying high-dimensional microarray gene expression data. Sparse group Lasso and its variants have been employed for gene selection to capture the interactions of genes within a group. Most of...
Neural networks : the official journal of the International Neural Network Society
Nov 8, 2023
In this paper, we propose a new short-term load forecasting (STLF) model based on contextually enhanced hybrid and hierarchical architecture combining exponential smoothing (ES) and a recurrent neural network (RNN). The model is composed of two simul...
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