With 98.4% accuracy in melanoma detection, SkinEHDLF demonstrates the potential of hybrid deep learning models in ...

The study begins by identifying key deficiencies in traditional spam filtering systems. Classic rule-based methods and machine learning classifiers such as Naïve Bayes, Support Vector Machines (SVM), ...

Sarvesh Kumar Gupta's has been marked by significant contributions to major data architecture projects, where he has honed ...

HealthSecureNet operates through a three-tiered machine learning architecture that combines Gradient Boosting and Support ...

A new “periodic table for machine learning,” is reshaping how researchers explore AI, unlocking fresh pathways for discovery.

This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...

Univ Rennes, CNRS, ISCR (Institut des Sciences Chimiques de Rennes)−UMR 6226, Rennes F-35000, France ...

Orbitofrontal cortex and hippocampus reinstate representations of causal choices to associate with delayed outcomes, and the frontal pole supports this credit assignment process by maintaining pending ...

He revealed that DeepMind has created an AI system capable of designing its own reinforcement learning algorithms. What’s more, these AI-generated algorithms have surpassed the performance of ...

To address the challenges, we propose a spectral-spatial representation learning (SSRL) framework based on HSI ... that the proposed algorithm outperforms state-of-art methods in classification ...