#efficientnet News & Analysis

4 articles tagged with #efficientnet. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

4 articles

AIBullisharXiv – CS AI · Mar 177/10

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RESQ: A Unified Framework for REliability- and Security Enhancement of Quantized Deep Neural Networks

Researchers propose RESQ, a three-stage framework that enhances both security and reliability of quantized deep neural networks through specialized fine-tuning techniques. The framework demonstrates up to 10.35% improvement in attack resilience and 12.47% in fault resilience while maintaining competitive accuracy across multiple neural network architectures.

AINeutralarXiv – CS AI · Jun 56/10

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Three-Dimensional Retinal Microvasculature Restoration in OCT Angiography

Researchers have developed a deep learning algorithm that restores three-dimensional retinal microvasculature from optical coherence tomographic angiography (OCTA) scans, significantly improving image quality and vascular clarity. Using an EfficientNet-B5 encoder with squeeze-and-excitation modules, the model achieves 26.16 PSNR and 0.91 SSIM scores, substantially outperforming standard OCTA imaging and enabling more accurate quantification of retinal blood flow for clinical diagnostics.

AINeutralarXiv – CS AI · Jun 26/10

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Attention mechanisms and transfer learning for robust peach leaf damage classification under domain shift

Researchers developed an AI-powered image classification system for detecting peach leaf damage using deep learning and attention mechanisms, achieving 93.3% accuracy on a benchmark dataset. The study demonstrates that EfficientNet models with attention modules provide robust generalization across different farming environments, addressing a critical need in automated agricultural disease diagnosis.

AINeutralarXiv – CS AI · Mar 164/10

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HSEmotion Team at ABAW-10 Competition: Facial Expression Recognition, Valence-Arousal Estimation, Action Unit Detection and Fine-Grained Violence Classification

HSEmotion Team developed a fast approach for facial emotion analysis using pre-trained EfficientNet models for the ABAW-10 competition. Their method combines confidence-based predictions with multi-layered perceptrons and sliding window smoothing, achieving significant improvements over existing baselines across four emotion recognition tasks.