AIMC Topic: Algorithms

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A Novel session-based recommendation system using capsule graph neural network.

Neural networks : the official journal of the International Neural Network Society
Session-based recommendation systems (SBRS) are essential for enhancing the customer experience, improving sales and loyalty, and providing the possibility to discover products in dynamic and real-world scenarios without needing user history. Despite...

Artificial Intelligence in Endoscopy Quality Measures.

Gastrointestinal endoscopy clinics of North America
Quality of gastrointestinal endoscopy is a major determinant of its effectiveness. Artificial intelligence (AI) has the potential to enhance quality monitoring and improve endoscopy outcomes. This article reviews the current literature on AI algorith...

Enhancing lesion detection in automated breast ultrasound using unsupervised multi-view contrastive learning with 3D DETR.

Medical image analysis
The inherent variability of lesions poses challenges in leveraging AI in 3D automated breast ultrasound (ABUS) for lesion detection. Traditional methods based on single scans have fallen short compared to comprehensive evaluations by experienced sono...

Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US.

Sensors (Basel, Switzerland)
Efficient and reliable corn ( L.) yield prediction is important for varietal selection by plant breeders and management decision-making by growers. Unlike prior studies that focus mainly on county-level or controlled laboratory-scale areas, this stud...

TagGen: Diffusion-based generative model for cardiac MR tagging super resolution.

Magnetic resonance in medicine
PURPOSE: The aim of the work is to develop a cascaded diffusion-based super-resolution model for low-resolution (LR) MR tagging acquisitions, which is integrated with parallel imaging to achieve highly accelerated MR tagging while enhancing the tag g...

A new pipeline with ultimate search efficiency for neural architecture search.

Neural networks : the official journal of the International Neural Network Society
We present a novel neural architecture search pipeline designed to enhance search efficiency through optimized data and algorithms. Leveraging dataset distillation techniques, our pipeline condenses large-scale target datasets into more streamlined p...

On latent dynamics learning in nonlinear reduced order modeling.

Neural networks : the official journal of the International Neural Network Society
In this work, we present the novel mathematical framework of latent dynamics models (LDMs) for reduced order modeling of parameterized nonlinear time-dependent PDEs. Our framework casts this latter task as a nonlinear dimensionality reduction problem...

When low-light meets flares: Towards Synchronous Flare Removal and Brightness Enhancement.

Neural networks : the official journal of the International Neural Network Society
Low-light image enhancement (LLIE) aims to improve the visibility and illumination of low-light images. However, real-world low-light images are usually accompanied with flares caused by light sources, which make it difficult to discern the content o...

Contrastive independent subspace analysis network for multi-view spatial information extraction.

Neural networks : the official journal of the International Neural Network Society
Multi-view classification integrates features from different views to optimize classification performance. Most of the existing works typically utilize semantic information to achieve view fusion but neglect the spatial information of data itself, wh...

Out-of-Distribution Detection via outlier exposure in federated learning.

Neural networks : the official journal of the International Neural Network Society
Among various out-of-distribution (OOD) detection methods in neural networks, outlier exposure (OE) using auxiliary data has shown to achieve practical performance. However, existing OE methods are typically assumed to run in a centralized manner, an...