EfficientNet-B3
PulseAugur coverage of EfficientNet-B3 — every cluster mentioning EfficientNet-B3 across labs, papers, and developer communities, ranked by signal.
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AI frameworks tackle plant disease diagnosis and fruit classification
Researchers have developed advanced AI frameworks for agricultural applications, focusing on plant disease diagnosis and fruit classification. The first study introduces H²MAF, which fuses vision models like EfficientNe…
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Deep learning framework decodes sex from prehistoric hand stencils
Researchers have developed a novel deep learning framework designed to determine the biological sex of individuals who created prehistoric hand stencils. This uncertainty-aware system addresses challenges like the lack …
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OrthKD framework extracts clinical knowledge for lightweight diabetic retinopathy screening
Researchers have developed OrthKD, a novel knowledge distillation framework designed to extract generalized clinical knowledge from heterogeneous AI models for lightweight deployment in diabetic retinopathy screening. T…
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New open-source system automates skeletal maturity assessment
Researchers have developed BoneAgeTW2, an open-source system designed to automate the Tanner-Whitehouse 2 (TW2) protocol for assessing skeletal maturity. The system utilizes YOLOv8 for bone detection and EfficientNet-B3…
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Class-wise dataset mixing boosts breast MRI tumor classification accuracy
Researchers have developed a method called Class-Wise Dataset Mixing to improve the generalization of deep learning models for breast MRI tumor classification. When models like EfficientNet-B3 and WaveViT-Small were tra…
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Blasto-Net: AI model for blastocyst analysis in IVF · 2 sources tracked
Researchers have developed Blasto-Net, a novel multi-task deep learning model designed for comprehensive blastocyst analysis in in vitro fertilization (IVF). This model simultaneously performs segmentation of key compar…
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Deep learning frameworks compared for rice disease mapping
Researchers compared various deep learning frameworks for mapping rice disease severity using UAV multispectral imagery. The study evaluated architectures like U-Net, U-Net++, DeepLabV3+, and SegFormer, testing them wit…
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AI model classifies wildfire smoke density with uncertainty estimates
Researchers have developed a new deep learning framework to classify wildfire smoke density from satellite imagery, categorizing it into light, moderate, and heavy severity. This model provides decomposed epistemic and …
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Simpler fusion modules outperform complex transformers for pasture biomass regression
A new research paper introduces the principle of "fusion complexity inversion," demonstrating that simpler cross-view fusion modules can outperform more complex ones like attention transformers and SSMs for pasture biom…
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AnemiaVision uses smartphone photos for non-invasive anemia detection
Researchers have developed AnemiaVision, a web-based system capable of detecting anemia using smartphone images of the palpebral conjunctiva and fingernail beds. The system fine-tunes an EfficientNet-B3 model, incorpora…