matlok
's Collections
Papers - ResNet
updated
Paper
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1605.07146
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Published
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2
Characterizing signal propagation to close the performance gap in
unnormalized ResNets
Paper
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2101.08692
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Published
•
2
Pareto-Optimal Quantized ResNet Is Mostly 4-bit
Paper
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2105.03536
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Published
•
2
When Vision Transformers Outperform ResNets without Pre-training or
Strong Data Augmentations
Paper
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2106.01548
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Published
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2
ResNet strikes back: An improved training procedure in timm
Paper
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2110.00476
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Published
•
2
A ResNet is All You Need? Modeling A Strong Baseline for Detecting
Referable Diabetic Retinopathy in Fundus Images
Paper
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2210.03180
•
Published
Deep Residual Learning for Image Recognition
Paper
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1512.03385
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Published
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6
Revisiting ResNets: Improved Training and Scaling Strategies
Paper
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2103.07579
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Published
•
2
Densely Connected Convolutional Networks
Paper
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1608.06993
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Published
•
3
Aggregated Residual Transformations for Deep Neural Networks
Paper
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1611.05431
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Published
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2
RTSeg: Real-time Semantic Segmentation Comparative Study
Paper
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1803.02758
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Published
•
2
Latent Diffusion Model for Medical Image Standardization and Enhancement
Paper
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2310.05237
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Published
•
2
3D Medical Image Segmentation based on multi-scale MPU-Net
Paper
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2307.05799
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Published
•
2
Joint Liver and Hepatic Lesion Segmentation in MRI using a Hybrid CNN
with Transformer Layers
Paper
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2201.10981
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Published
•
2
Bootstrap your own latent: A new approach to self-supervised Learning
Paper
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2006.07733
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Published
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2
From Modern CNNs to Vision Transformers: Assessing the Performance,
Robustness, and Classification Strategies of Deep Learning Models in
Histopathology
Paper
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2204.05044
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Published
•
2
Self-Supervised Vision Transformers Learn Visual Concepts in
Histopathology
Paper
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2203.00585
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Published
•
2
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Paper
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1905.11946
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Published
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3
DAS: A Deformable Attention to Capture Salient Information in CNNs
Paper
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2311.12091
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Published
•
2
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for
White Blood Cells
Paper
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2401.07278
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Published
•
2
Adding Conditional Control to Text-to-Image Diffusion Models
Paper
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2302.05543
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Published
•
40
Data Distributional Properties Drive Emergent In-Context Learning in
Transformers
Paper
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2205.05055
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Published
•
2
CascadeTabNet: An approach for end to end table detection and structure
recognition from image-based documents
Paper
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2004.12629
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Published
•
2
Realism in Action: Anomaly-Aware Diagnosis of Brain Tumors from Medical
Images Using YOLOv8 and DeiT
Paper
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2401.03302
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Published
•
1
Detecting and recognizing characters in Greek papyri with YOLOv8, DeiT
and SimCLR
Paper
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2401.12513
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Published
•
1
DeiT-LT Distillation Strikes Back for Vision Transformer Training on
Long-Tailed Datasets
Paper
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2404.02900
•
Published
•
1
DeiT III: Revenge of the ViT
Paper
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2204.07118
•
Published
•
1
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Paper
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2404.07448
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Published
•
11
ConsistencyDet: Robust Object Detector with Denoising Paradigm of
Consistency Model
Paper
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2404.07773
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Published
•
1
Long-form music generation with latent diffusion
Paper
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2404.10301
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Published
•
24
GLIGEN: Open-Set Grounded Text-to-Image Generation
Paper
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2301.07093
•
Published
•
3
A Multimodal Automated Interpretability Agent
Paper
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2404.14394
•
Published
•
20
What needs to go right for an induction head? A mechanistic study of
in-context learning circuits and their formation
Paper
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2404.07129
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Published
•
3
Multiplication-Free Transformer Training via Piecewise Affine Operations
Paper
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2305.17190
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Published
•
2
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Paper
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1809.11096
•
Published
•
1
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
Paper
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1707.02968
•
Published
•
1
Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept
Space
Paper
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2406.19370
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Published
•
1
Paper
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2303.14027
•
Published
•
1
Equivariant Transformer Networks
Paper
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1901.11399
•
Published
•
1
Fixup Initialization: Residual Learning Without Normalization
Paper
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1901.09321
•
Published
•
1
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and
Out Distribution Robustness
Paper
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2206.14502
•
Published
•
1