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Collections including paper arxiv:2307.05799
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3D Medical Image Segmentation based on multi-scale MPU-Net
Paper • 2307.05799 • Published • 2 -
Joint Liver and Hepatic Lesion Segmentation in MRI using a Hybrid CNN with Transformer Layers
Paper • 2201.10981 • Published • 2 -
Using Multi-scale SwinTransformer-HTC with Data augmentation in CoNIC Challenge
Paper • 2202.13588 • Published • 2
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H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
Paper • 1709.07330 • Published • 2 -
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
Paper • 1801.08599 • Published • 2 -
Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function
Paper • 1810.09488 • Published • 2 -
Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets
Paper • 1901.11369 • Published • 2
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Image Segmentation using U-Net Architecture for Powder X-ray Diffraction Images
Paper • 2310.16186 • Published • 2 -
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
Paper • 1709.07330 • Published • 2 -
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
Paper • 1801.08599 • Published • 2 -
RTSeg: Real-time Semantic Segmentation Comparative Study
Paper • 1803.02758 • Published • 2
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Paper • 1505.04597 • Published • 7 -
Image Segmentation using U-Net Architecture for Powder X-ray Diffraction Images
Paper • 2310.16186 • Published • 2 -
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
Paper • 1709.07330 • Published • 2 -
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
Paper • 1801.08599 • Published • 2
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Wide Residual Networks
Paper • 1605.07146 • Published • 2 -
Characterizing signal propagation to close the performance gap in unnormalized ResNets
Paper • 2101.08692 • Published • 2 -
Pareto-Optimal Quantized ResNet Is Mostly 4-bit
Paper • 2105.03536 • Published • 2 -
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations
Paper • 2106.01548 • Published • 2
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FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation
Paper • 2403.06775 • Published • 3 -
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Paper • 2010.11929 • Published • 6 -
Data Incubation -- Synthesizing Missing Data for Handwriting Recognition
Paper • 2110.07040 • Published • 2 -
A Mixture of Expert Approach for Low-Cost Customization of Deep Neural Networks
Paper • 1811.00056 • Published • 2
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Linear Transformers with Learnable Kernel Functions are Better In-Context Models
Paper • 2402.10644 • Published • 78 -
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Paper • 2305.13245 • Published • 5 -
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition
Paper • 2402.15220 • Published • 19 -
Sequence Parallelism: Long Sequence Training from System Perspective
Paper • 2105.13120 • Published • 5