Nermeen Abou Baker
PulseAugur coverage of Nermeen Abou Baker — every cluster mentioning Nermeen Abou Baker across labs, papers, and developer communities, ranked by signal.
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AI model boosts e-waste recycling accuracy to 98% · 2 sources tracked
Researchers have developed a transfer learning method using AI to improve the accuracy and efficiency of e-waste recycling. By fine-tuning the AlexNet model, they achieved nearly 98% accuracy in classifying smartphone e…
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Transfer learning boosts X-ray battery detection to 94% precision
Researchers have developed a transfer learning approach for detecting and classifying batteries in X-ray images. The method utilizes a pre-trained YOLOv5m model, fine-tuned on a dataset for electronic device detection, …
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Meta's SAM fine-tuned for improved waste segmentation accuracy
Researchers have explored the effectiveness of Meta AI's Segment Anything Model (SAM) for waste segmentation tasks. By fine-tuning SAM on three specific waste datasets, they found that the SAM-ViT-H model significantly …
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PEFT methods boost instance segmentation with minimal parameter tuning
Researchers have investigated parameter-efficient fine-tuning (PEFT) methods, specifically adapters and LoRA, for transformer-based models in instance segmentation tasks. The study found that these techniques can achiev…
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Study evaluates transfer learning for deep neural networks in image classification
Researchers explored how to best select pre-trained deep neural networks for image classification tasks. They adapted eleven models, originally trained on ImageNet, to five distinct target datasets. The study evaluated …