Image Segmentation using U-Net Architecture for Powder X-ray Diffraction Images
Paper
• 2310.16186 • Published
• 2
Papers - Image - Segmentation
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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 -
RTSeg: Real-time Semantic Segmentation Comparative Study
Paper • 1803.02758 • Published • 2 -
Generalizability vs. Robustness: Adversarial Examples for Medical Imaging
Paper • 1804.00504 • Published • 2 -
Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function
Paper • 1810.09488 • Published • 2 -
IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet
Paper • 1811.08305 • Published • 2 -
A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images
Paper • 1905.10835 • Published • 3 -
Enforcing temporal consistency in Deep Learning segmentation of brain MR images
Paper • 1906.07160 • Published • 3 -
SkipNet: Learning Dynamic Routing in Convolutional Networks
Paper • 1711.09485 • Published • 2 -
Bias Loss for Mobile Neural Networks
Paper • 2107.11170 • Published • 2 -
Skip-Connected Neural Networks with Layout Graphs for Floor Plan Auto-Generation
Paper • 2309.13881 • Published • 2 -
Head and Neck Tumor Segmentation from [18F]F-FDG PET/CT Images Based on 3D Diffusion Model
Paper • 2401.17593 • Published • 3 -
Inter-Scale Dependency Modeling for Skin Lesion Segmentation with Transformer-based Networks
Paper • 2310.13727 • Published • 2 -
3D Medical Image Segmentation based on multi-scale MPU-Net
Paper • 2307.05799 • Published • 2 -
Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation
Paper • 2210.16898 • Published • 2 -
Self-Supervised U-Net for Segmenting Flat and Sessile Polyps
Paper • 2110.08776 • Published • 2 -
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images
Paper • 2106.05843 • Published • 2 -
Saliency-Guided Deep Learning Network for Automatic Tumor Bed Volume Delineation in Post-operative Breast Irradiation
Paper • 2105.02771 • Published • 2 -
Qutrit-inspired Fully Self-supervised Shallow Quantum Learning Network for Brain Tumor Segmentation
Paper • 2009.06767 • Published • 2 -
The Effects of Image Pre- and Post-Processing, Wavelet Decomposition, and Local Binary Patterns on U-Nets for Skin Lesion Segmentation
Paper • 1805.05239 • Published • 2 -
A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs
Paper • 1908.08588 • Published • 2 -
Joint Liver and Hepatic Lesion Segmentation in MRI using a Hybrid CNN with Transformer Layers
Paper • 2201.10981 • Published • 2 -
Meta-information-aware Dual-path Transformer for Differential Diagnosis of Multi-type Pancreatic Lesions in Multi-phase CT
Paper • 2303.00942 • Published • 2 -
Cross-Shaped Windows Transformer with Self-supervised Pretraining for Clinically Significant Prostate Cancer Detection in Bi-parametric MRI
Paper • 2305.00385 • Published • 2 -
MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition
Paper • 2209.01620 • Published • 2 -
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Paper • 2103.14030 • Published • 5 -
A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images
Paper • 2104.12137 • Published • 2 -
Self-Supervised Learning with Swin Transformers
Paper • 2105.04553 • Published • 3 -
Bootstrap your own latent: A new approach to self-supervised Learning
Paper • 2006.07733 • Published • 2 -
Using Multi-scale SwinTransformer-HTC with Data augmentation in CoNIC Challenge
Paper • 2202.13588 • Published • 2 -
From Modern CNNs to Vision Transformers: Assessing the Performance, Robustness, and Classification Strategies of Deep Learning Models in Histopathology
Paper • 2204.05044 • Published • 2 -
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology
Paper • 2203.00585 • Published • 3 -
GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection
Paper • 2104.14528 • Published • 2 -
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cells
Paper • 2401.07278 • Published • 2 -
Unifying Vision, Text, and Layout for Universal Document Processing
Paper • 2212.02623 • Published • 11 -
Segment Anything
Paper • 2304.02643 • Published • 5 -
Noise-Aware Training of Layout-Aware Language Models
Paper • 2404.00488 • Published • 10 -
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Paper • 2404.07448 • Published • 12 -
RegionGPT: Towards Region Understanding Vision Language Model
Paper • 2403.02330 • Published • 2 -
COCONut: Modernizing COCO Segmentation
Paper • 2404.08639 • Published • 30 -
Efficient Transformer Encoders for Mask2Former-style models
Paper • 2404.15244 • Published • 1 -
Mask2Former for Video Instance Segmentation
Paper • 2112.10764 • Published • 1 -
Deep Residual Learning for Image Recognition
Paper • 1512.03385 • Published • 12 -
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 29 -
Interactive3D: Create What You Want by Interactive 3D Generation
Paper • 2404.16510 • Published • 21 -
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks
Paper • 2311.06242 • Published • 95 -
SAM 2: Segment Anything in Images and Videos
Paper • 2408.00714 • Published • 120 -
Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning
Paper • 2408.07931 • Published • 22 -
Medical SAM 2: Segment medical images as video via Segment Anything Model 2
Paper • 2408.00874 • Published • 52