AIMC Topic: Algorithms

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Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning.

PLoS computational biology
Oxygenic photosynthesis is responsible for nearly all biomass production on Earth, and may have been a prerequisite for establishing a complex biosphere rich in multicellular life. Life on Earth has evolved to perform photosynthesis in a wide range o...

Early warning strategies for corporate operational risk: A study by an improved random forest algorithm using FCM clustering.

PloS one
To enhance the accuracy and response speed of the risk early warning system, this study develops a novel early warning system that combines the Fuzzy C-Means (FCM) clustering algorithm and the Random Forest (RF) model. Firstly, based on operational r...

A fuzzy robust optimization model for dual objective forward and reverse logistics networks considering carbon emissions.

PloS one
The inherent unpredictability within the low-carbon integrated supply chain logistics network complicates its management. This paper endeavours to address the challenge of designing a low-carbon logistics network within a context of uncertainty and w...

Iris Geometric Transformation Guided Deep Appearance-Based Gaze Estimation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The geometric alterations in the iris's appearance are intricately linked to the gaze direction. However, current deep appearance-based gaze estimation methods mainly rely on latent feature sharing to leverage iris features for improving deep represe...

Global Cross-Entropy Loss for Deep Face Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Contemporary deep face recognition techniques predominantly utilize the Softmax loss function, designed based on the similarities between sample features and class prototypes. These similarities can be categorized into four types: in-sample target si...

deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria.

mSystems
Selenoproteins are a special group of proteins with major roles in cellular antioxidant defense. They contain the 21st amino acid selenocysteine (Sec) in the active sites, which is encoded by an in-frame UGA codon. Compared to eukaryotes, identificat...

An intelligent multi-attribute decision-making system for clinical assessment of spinal cord disorder using fuzzy hypersoft rough approximations.

BMC medical informatics and decision making
The data for diagnosing spinal cord disorder (SCD) are complex and often confusing, making it difficult for established diagnostic techniques to yield reliable results. This issue frequently necessitates expensive testing to get an accurate diagnosis...

Genomic selection in pig breeding: comparative analysis of machine learning algorithms.

Genetics, selection, evolution : GSE
BACKGROUND: The effectiveness of genomic prediction (GP) significantly influences breeding progress, and employing SNP markers to predict phenotypic values is a pivotal aspect of pig breeding. Machine learning (ML) methods are usually used to predict...

Dual-branch dynamic hierarchical U-Net with multi-layer space fusion attention for medical image segmentation.

Scientific reports
Accurate segmentation of organs or lesions from medical images is essential for accurate disease diagnosis and organ morphometrics. Previously, most researchers mainly added feature extraction modules and simply aggregated the semantic features to U-...

Pixel level deep reinforcement learning for accurate and robust medical image segmentation.

Scientific reports
Existing deep learning methods have achieved significant success in medical image segmentation. However, this success largely relies on stacking advanced modules and architectures, which has created a path dependency. This path dependency is unsustai...