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AI Researchers Propose A Method Using Irregular Pupil Shapes To Identify...

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Computer-generated faces have lately improved to the point that they are difficult to tell apart from the real thing. That makes them a handy...

University of Tübingen Researchers Open-Source ‘CARLA’, A Python Library for Benchmarking...

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Machine learning methods are applied to everyday life in various ways, from disease diagnostics, criminal justice and credit risk scoring. Machine learning models have...

MIT Researchers Introduce ‘MedKnowts’, A System That Combines Machine Learning And...

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Electronic health records (EHRs) have become widely used in the hopes of saving time and improving patient care quality. Physicians, however, typically spend more...

Russian Bioinformaticians Have Created A Neural Network Architecture That Can Evaluate...

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A novel neural network design to assess how successfully a guide RNA has been chosen for a gene-editing procedure. This methodology will allow for...

KAUST Researchers Introduce ‘OmniReduce’, A New Way To Improve Machine Learning...

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Researchers from KAUST (King Abdullah University of Science and Technology) have found a new way to remarkably increase the training speed of machine learning...

Hierarchical Federated Learning-Based Anomaly Detection Using Digital Twins For Internet of...

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Smart healthcare services can be provided by using Internet of Things (IoT) technologies that monitor the health conditions of patients and their vital body...

Israeli Researchers Unveil DeepSIM, a Neural Generative Model for Conditional Image...

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In recent years, deep neural networks have been proven effective at performing image manipulation tasks for which large training datasets are available such as,...

A New AI Research Propose ‘UniFormer’ (Unified transFormer) to Unify Convolution...

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For visual recognition, representation learning is a crucial research area. Essentially, researchers are confronted with two separate issues in visual data, such as photographs...

Researchers From Heidelberg and University of Bern Propose A New Method...

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A technique to achieve quick and energy-efficient computing using the concept of spiking is ground-breaking in research. When the membrane potential, an attribute related...

Researchers Introduce ‘AugMax’: An Open-Sourced Data Augmentation Framework To Unify The...

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Data augmentation Data augmentation in machine learning is a technique that helps reduce overfitting. It increases the amount of data by adding slightly modified copies...