EfficientNet-B5
PulseAugur coverage of EfficientNet-B5 — every cluster mentioning EfficientNet-B5 across labs, papers, and developer communities, ranked by signal.
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AI framework aids in diagnosing hair loss conditions
Researchers have developed an AI-driven framework to quantitatively analyze scalp conditions, specifically focusing on androgenetic alopecia (AGA). This system combines multiple stages, including follicular unit localiz…
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Pretraining and Distillation Outperform Architecture Choice in Cell Classification
A new study published on arXiv investigates the effectiveness of different deep learning architectures for label-free single-cell classification. The research found that pretraining and fine-tuning strategies are more c…
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DualMiT-Net enhances breast mass segmentation with dual-branch AI
Researchers have developed DualMiT-Net, a novel deep learning model for segmenting breast masses in mammograms. This dual-branch network combines a focused view of the mass with a broader context of the surrounding brea…
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New framework enhances explainability for AI in retinal disease detection
Researchers have developed CounterFundus, a novel framework for explaining deep learning models used in retinal disease classification. This framework utilizes CycleGAN to generate counterfactual explanations, translati…
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AI mammography models learn dataset origin, not just disease
A new study published on arXiv explores the impact of dataset origin on AI models used for screening mammography. Researchers found that supplementing a primary dataset (NLBSD) with biopsy-confirmed cases from external,…
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Deep learning restores 3D retinal microvasculature from OCTA scans
Researchers have developed a novel deep learning algorithm to reconstruct the intricate three-dimensional microvasculature of the retina from single OCT Angiography (OCTA) volumes. This method utilizes an EfficientNet-B…
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KAYRA AI system offers flexible cloud/on-premise deployment for karyotyping
Researchers have developed KAYRA, a microservice architecture for AI-assisted karyotyping designed for clinical cytogenetic laboratories. The system integrates multiple machine learning models, including semantic segmen…
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Researchers identify concept inconsistency in dermoscopic models, impacting accuracy.
Researchers have identified significant concept-level inconsistencies within the Derm7pt dermoscopy dataset, which limit the accuracy of Concept Bottleneck Models (CBMs). By applying rough set theory, they found that 16…