Dieter
@kagglingdieter.bsky.social
deep learner @nvidia, PhD mathematics, current rank @kaggle: 1
The solution in an ensemble of segmentation (3D Unets with ResNet & B3 encoders) and object detection models (SegResNet and DynUnet backbones) from MONAI.
We accelerate model inference with TensorRT to achieve 200% speedup compared to eager PyTorch runtime
We accelerate model inference with TensorRT to achieve 200% speedup compared to eager PyTorch runtime
February 7, 2025 at 12:48 PM
The solution in an ensemble of segmentation (3D Unets with ResNet & B3 encoders) and object detection models (SegResNet and DynUnet backbones) from MONAI.
We accelerate model inference with TensorRT to achieve 200% speedup compared to eager PyTorch runtime
We accelerate model inference with TensorRT to achieve 200% speedup compared to eager PyTorch runtime
This competition challenged us to detect and classify five classes of protein complexes within a real-world cryoET dataset—pushing the boundaries of deep learning in structural biology.
February 7, 2025 at 12:48 PM
This competition challenged us to detect and classify five classes of protein complexes within a real-world cryoET dataset—pushing the boundaries of deep learning in structural biology.
Cryo-electron tomography (cryoET) generates high-resolution 3D tomograms, capturing proteins in their native, highly crowded cellular environment. It has immense potential to unlock the mysteries of the cell.
February 7, 2025 at 12:48 PM
Cryo-electron tomography (cryoET) generates high-resolution 3D tomograms, capturing proteins in their native, highly crowded cellular environment. It has immense potential to unlock the mysteries of the cell.