AIMC Topic: Machine Learning

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Prospects and Challenges of Using Machine Learning for Academic Forecasting.

Computational intelligence and neuroscience
The study examines the prospects and challenges of machine learning (ML) applications in academic forecasting. Predicting academic activities through machine learning algorithms presents an enhanced means to accurately forecast academic events, inclu...

Comparison of Transfer Learning Models in Pelvic Tilt and Rotation Measurement in Pediatric Anteroposterior Pelvic Radiographs.

Journal of digital imaging
The rotation and tilt of the pelvis during anteroposterior pelvic radiography can lead to misdiagnosis of developmental dysplasia of the hip (DDH) in children. At present, no method exists for accurately and conveniently measuring the precise rotatio...

A universal adversarial policy for text classifiers.

Neural networks : the official journal of the International Neural Network Society
Discovering the existence of universal adversarial perturbations had large theoretical and practical impacts on the field of adversarial learning. In the text domain, most universal studies focused on adversarial prefixes which are added to all texts...

A Hybrid Machine Learning Approach for Structure Stability Prediction in Molecular Co-crystal Screenings.

Journal of chemical theory and computation
Co-crystals are a highly interesting material class as varying their components and stoichiometry in principle allows tuning supramolecular assemblies toward desired physical properties. The prediction of co-crystal structures represents a daunting ...

Exploring Potential Energy Surfaces Using Reinforcement Machine Learning.

Journal of chemical information and modeling
Reinforcement machine learning is implemented to survey a series of model potential energy surfaces and ultimately identify the global minima point. Through sophisticated reward function design, the introduction of an optimizing target, and incorpora...

A Review of Image Processing Techniques for Deepfakes.

Sensors (Basel, Switzerland)
Deep learning is used to address a wide range of challenging issues including large data analysis, image processing, object detection, and autonomous control. In the same way, deep learning techniques are also used to develop software and techniques ...

Online Domain Adaptation for Rolling Bearings Fault Diagnosis with Imbalanced Cross-Domain Data.

Sensors (Basel, Switzerland)
Traditional machine learning methods rely on the training data and target data having the same feature space and data distribution. The performance may be unacceptable if there is a difference in data distribution between the training and target data...

RETRACTED: Triaging Medical Referrals Based on Clinical Prioritisation Criteria Using Machine Learning Techniques.

International journal of environmental research and public health
Triaging of medical referrals can be completed using various machine learning techniques, but trained models with historical datasets may not be relevant as the clinical criteria for triaging are regularly updated and changed. This paper proposes the...