AIMC Topic: Algorithms

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Mapping of groundwater salinization and modelling using meta-heuristic algorithms for the coastal aquifer of eastern Saudi Arabia.

The Science of the total environment
The growing increase in groundwater (GW) salinization in the coastal aquifers has reached an alarming socio-economic menace in Saudi Arabia and various places globally due to several natural and anthropogenic activities. Hence, evaluating the GW sali...

Deep Learning for Image Enhancement and Correction in Magnetic Resonance Imaging-State-of-the-Art and Challenges.

Journal of digital imaging
Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical diagnoses and research which underpin many recent breakthroughs in medicine and biology. The post-processing of reconstructed MR images is often automated for incor...

An explainable deep learning-based algorithm with an attention mechanism for predicting the live birth potential of mouse embryos.

Artificial intelligence in medicine
In assisted reproductive technology (ART), embryos produced by in vitro fertilization (IVF) are graded according to their live birth potential, and high-grade embryos are preferentially transplanted. However, rates of live birth following clinical AR...

Deep Learning-Based Intelligent Forklift Cargo Accurate Transfer System.

Sensors (Basel, Switzerland)
In this research, we present an intelligent forklift cargo precision transfer system to address the issue of poor pallet docking accuracy and low recognition rate when using current techniques. The technology is primarily used to automatically check ...

Intrusion Detection in IoT Using Deep Learning.

Sensors (Basel, Switzerland)
Cybersecurity has been widely used in various applications, such as intelligent industrial systems, homes, personal devices, and cars, and has led to innovative developments that continue to face challenges in solving problems related to security met...

Self-supervised machine learning for live cell imagery segmentation.

Communications biology
Segmenting single cells is a necessary process for extracting quantitative data from biological microscopy imagery. The past decade has seen the advent of machine learning (ML) methods to aid in this process, the overwhelming majority of which fall u...

Explainable Deep-Learning-Assisted Sweat Assessment via a Programmable Colorimetric Chip.

Analytical chemistry
Multianalytes and individual differences of biofluids (such as blood, urine, or sweat) pose enormous complexity and challenges to rapid, facile, high-throughput, and accurate clinical analysis or health assessment. Deep-learning (DL)-assisted image a...

Optimizing Face Recognition Inference with a Collaborative Edge-Cloud Network.

Sensors (Basel, Switzerland)
The rapid development of deep-learning-based edge artificial intelligence applications and their data-driven nature has led to several research issues. One key issue is the collaboration of the edge and cloud to optimize such applications by increasi...

Machine learning in medicine: a practical introduction to techniques for data pre-processing, hyperparameter tuning, and model comparison.

BMC medical research methodology
BACKGROUND: There is growing enthusiasm for the application of machine learning (ML) and artificial intelligence (AI) techniques to clinical research and practice. However, instructions on how to develop robust high-quality ML and AI in medicine are ...

The effect of self-organizing map architecture based on the value migration network centrality measures on stock return. Evidence from the US market.

PloS one
Complex financial systems are the subject of current research interest. The notion of complex network is used for understanding the value migration process. Based on the stock data of 498 companies listed in the S&P500, the value migration network ha...