AIMC Topic: Algorithms

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Learning to Program "Recycles" Preexisting Frontoparietal Population Codes of Logical Algorithms.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Computer programming is a cornerstone of modern society, yet little is known about how the human brain enables this recently invented cultural skill. According to the neural recycling hypothesis, cultural skills (e.g., reading, math) repurpose preexi...

Evaluating machine learning approaches for host prediction using H3 influenza genomic data.

PloS one
BACKGROUND: H3 influenza A viruses (IAV) have been shown to frequently cross the species barrier which can be an important factor in sustained transmission and spread. Machine learning methods have been widely explored for host prediction of IAV usin...

FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment.

PloS one
Driver drowsiness is a leading cause of traffic accidents and fatalities, highlighting the urgent need for intelligent systems capable of real-time fatigue detection. Although recent advancements in machine learning (ML) and deep learning (DL) have s...

Interpretable weakly-supervised learning through kernel density matrices: A digital pathology use case.

PloS one
Classification methods based on deep learning require selecting between fully-supervised or weakly-supervised approaches, each presenting limitations in uncertainty quantification and interpretability. A framework unifying both supervision modes whil...

Comparative evaluation of score criteria for dynamic Bayesian Network structure learning.

PloS one
Dynamic Bayesian Networks (DBNs) are probabilistic models with a directional structure employed to model temporal processes. Three approaches to DBN structure learning are constraint-based, score-based, and hybrid. The score criterion determined in t...

Optimization of house price evaluation model based on multi-source geographic big data and deep neural network.

PloS one
The real estate market requires effective and precise house price prediction, as conventional models often face difficulties in generalization, computational efficiency, and interpretability. The research problem is addressed by introducing the House...

Football sports automatic judgment model based on improved YOLOv7 and RNN.

PloS one
The extraction, classification, and judgment of sports video scenes can improve work efficiency and accuracy. To understand sports videos in dynamic scenes, this study applies deep learning technology, firstly introducing clustering algorithm and att...

Development of a diagnostic model for ovarian cancer based on machine learning algorithms and functional analysis of key biomarker SOX17.

Journal of ovarian research
BACKGROUND: Ovarian cancer (OC) demonstrates the poorest prognosis among gynecological malignancies, with five-year survival rates below 45%, primarily due to late-stage diagnosis. To address this challenge, we systematically identified OC-specific d...

Training convolutional neural networks with the Forward-Forward Algorithm.

Scientific reports
Recent successes in image analysis with deep neural networks are achieved almost exclusively with Convolutional Neural Networks (CNNs), typically trained using the backpropagation (BP) algorithm. In a 2022 preprint, Geoffrey Hinton proposed the Forwa...

An interpretable crop leaf disease and pest identification model based on prototypical part network and contrastive learning.

Scientific reports
The disease and pest recognition algorithms based on computer vision can automatically process and analyze a large amount of disease and pest images, thereby achieving rapid and accurate identification of disease and pest categories on crop leaves. C...