Albumentations

List of papers that cite Albumentations

1. Automatic instrument segmentation in robot-assisted surgery using deep learning

- AA Shvets, A Rakhlin, AA Kalinin

2. Angiodysplasia detection and localization using deep convolutional neural networks

- AA Shvets, VI Iglovikov, A Rakhlin

3. Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better

- O Kupyn, T Martyniuk, J Wu

4. AutoML: A Survey of the State-of-the-Art

- X He, K Zhao, X Chu

5. Self-supervised learning for dense depth estimation in monocular endoscopy

- X Liu, A Sinha, M Unberath, M Ishii, GD Hager

6. Camera model identification using convolutional neural networks

- A Kuzin, A Fattakhov, I Kibardin

7. Transformation-Consistent Self-Ensembling Model for Semisupervised Medical Image Segmentation

- X Li, L Yu, H Chen, CW Fu, L Xing

8. U-NetPlus: a modified encoder-decoder U-Net architecture for semantic and instance segmentation of surgical instrument

- SM Hasan, CA Linte

9. Deep convolutions for in-depth automated rock typing

- EE Baraboshkin, LS Ismailova, DM Orlov

10. Automatic salt deposits segmentation: A deep learning approach

- M Karchevskiy, I Ashrapov, L Kozinkin

11. Semi-supervised segmentation of salt bodies in seismic images using an ensemble of convolutional neural networks

- Y Babakhin, A Sanakoyeu, H Kitamura

12. Breast tumor cellularity assessment using deep neural networks

- A Rakhlin, A Tiulpin, AA Shvets

13. General purpose (GenP) bioimage ensemble of handcrafted and learned features with data augmentation

- L Nanni, S Brahnam, S Ghidoni, G Maguolo

14. CLoDSA: a tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks

- Á Casado-García, C Domínguez

15. Data augmentation from RGB to chlorophyll fluorescence imaging Application to leaf segmentation of Arabidopsis thaliana from top view images

- N Sapoukhina, S Samiei, P Rasti

16. A framework for knowing who is doing what in aerial surveillance videos

- F Yang, S Sakti, Y Wu, S Nakamura

17. U-NetPlus: A modified encoder-decoder U-Net architecture for semantic and instance segmentation of surgical instruments from laparoscopic images

- SMK Hasan, CA Linte

18. Moiré pattern removal via attentive fractal network

- D Xu, Y Chu, Q Sun

19. Real-time tracking of guidewire robot tips using deep convolutional neural networks on successive localized frames

- I Ullah, P Chikontwe, SH Park

20. Road Segmentation using U-Net architecture

- NYQ Abderrahim, S Abderrahim

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21. A load frame for in situ tomography at PETRA III

- J Moosmann, DCF Wieland

22. Adapting Convolutional Neural Networks for Geographical Domain Shift

- P Ostyakov, SI Nikolenko

23. COVID-19 Prediction and Detection Using Deep Learning

- M Alazab, A Awajan, A Mesleh

24. Dense Dilated Convolutions' Merging Network for Land Cover Classification

- Q Liu, M Kampffmeyer, R Jenssen

25. StandardGAN: Multi-source Domain Adaptation for Semantic Segmentation of Very High Resolution Satellite Images by Data Standardization

- O Tasar, Y Tarabalka, A Giros

26. The Impact of Padding on Image Classification by Using Pre-trained Convolutional Neural Networks

- H Tang, A Ortis, S Battiato

27. Bayesian feature pyramid networks for automatic multi-label segmentation of chest X-rays and assessment of cardio-thoratic ratio

- R Solovyev, I Melekhov, T Lesonen

28. Safe augmentation: Learning task-specific transformations from data

- I Baran, O Kupyn, A Kravchenko

29. EasyAug: An automatic textual data augmentation platform for classification tasks

- S Qiu, B Xu, J Zhang, Y Wang, X Shen

30. The Effects of Augmented Training Dataset on Performance of Convolutional Neural Networks in Face Recognition System

- MA Kutlugün, Y Sirin

31. Greenhouse Segmentation on High-Resolution Optical Satellite Imagery using Deep Learning Techniques

- O Baghirli, I Ibrahimli, T Mammadzada

32. On-line hazard detection algorithm for precision lunar landing using semantic segmentation

- R Moghe, R Zanetti

33. Deep Learning object detection architectures in ADAS

- UO Etxabe, AG Basauri

34. Video Face Manipulation Detection Through Ensemble of CNNs

- N Bonettini, ED Cannas, S Mandelli, L Bondi

35. Retinopathy Diagnosis Using Semi-supervised Multi-channel Generative Adversarial Network

- Y Xie, Q Wan, G Chen, Y Xu, B Lei

36. Method for Whale Re-identification Based on Siamese Nets and Adversarial Training

- W Wang, RA Solovyev, AL Stempkovsky

37. Neural Mesh Refiner for 6-DoF Pose Estimation

- D Wu, Y Chen, X Qi, Y Jian, W Chen, R Xiao

38. 2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge

- Y Gu, Y Pan, S Chen

39. A Battery-Powered Friend: Towards Embedded Emotion Recognition

- P Shved

40. Analysis of medical images using deep learning

- A Utegulov

41. Online Augmentation for Quality Improvement of Neural Networks for Classification of Single-Channel Electrocardiograms

- V Guryanova

42. Artificial Intelligence in Quantitative Ultrasound Imaging: A Review

- B Zhou, X Yang, T Liu

43. Estimating Displaced Populations from Overhead

- A Hadzic, G Christie, J Freeman, A Dismer

44. Landslide Segmentation with U-Net: Evaluating Different Sampling Methods and Patch Sizes

- LP Soares, HC Dias, CH Grohmann

45. Segmentation of the Left Ventricle on EchoCG Images Using MultiResUnet

- A Sheka, V Samun, T Chumarnaya

46. Benchmark for Generic Product Detection: A strong baseline for Dense Object Detection

- S Varadarajan, S Kant, MM Srivastava

47. The Inclusive Images Competition

- J Atwood, Y Halpern, P Baljekar, E Breck

48. How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning?

- S Koehler, A Tandon, T Hussain, H Latus

49. Automatic Sorting of Dwarf Minke Whale Underwater Images

- DA Konovalov, N Swinhoe, DB Efremova, RA Birtles

50. Deep learning for skin lesion classification: augment, train, and ensemble= Aprendizado profundo para classificação de lesões de pele: aumento, treino e conjunto

- FVM Perez

51. Data Preprocessing via Multi-sequences MRI Mixture to Improve Brain Tumor Segmentation

- V Groza, B Tuchinov, E Pavlovskiy, E Amelina

52. Physical Cue based Depth-Sensing by Color Coding with Deaberration Network

- N Mishima, T Kozakaya, A Moriya, R Okada

53. Cloud Recognition and Masking of Earth Observation Imagery-An Optimized approach for Automatic Labeling of Sentinel-2 Imagery for Object Detection

- LM Ellefsen

54. Deep Learning for Skin Lesion Classification: Augment, Train, and Ensemble

- FVM Perez

55. Automation of Kidney Perfusion Analysis from Dynamic Phase-Contrast MRI using Deep Learning

- AM MORA

56. Semantic Segmentation of Smartphone Wound Images: Comparative Analysis of AHRF and CNN-Based Approaches WPI Technical Report WPI-CS-TR-19-02

- A Wagh

57. Weighted Ensemble Object Detection with Optimized Coefficients for Remote Sensing Images

- A Körez, N Barışçı, A Çetin, U Ergün

58. A Deep 3D Object Pose Estimation Framework for Robots with RGB-D Sensors

- AY Wagh

59. Urban Sound Tagging using Convolutional Neural Networks

- S Adapa

60. Seismic Interpretation of Partially Labeled 3D Cube with Neural Networks

- A Zhuchkov, D Prokhorov, V Gusev

61. How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalize to rare congenital heart diseases for surgical planning?

- S Koehler, A Tandon, T Hussain

62. Encoder-Recurrent Decoder Network for Single Image Dehazing

- A Dang, TH Vu, JC Wang

63. Working with scale: 2nd place solution to Product Detection in Densely Packed Scenes [Technical Report]

- A Kozlov

64. Challenges in the deep learning-based semantic segmentation of benthic communities from Ortho-images

- G Pavoni, M Corsini, N Pedersen, V Petrovic

65. CRNNS FOR URBAN SOUND TAGGING WITH SPATIOTEMPORAL CONTEXT

- A Arnault, IMTL Douai, N Riche

66. Endoscopy Artefact Detection and Segmentation using Deep Convolutional Neural Network.

- H Chen, C Lian, L Wang

67. End-to-end learning for semiquantitative rating of COVID-19 severity on Chest X-rays

- A Signoroni, M Savardi, S Benini, N Adami

68. GAN-SMOTE: A Generative Adversarial Network approach to Synthetic Minority Oversampling for One-Hot Encoded Data

- M Scott, J Plested

69. DLDENet: Deep Local Directional Embeddings with Increased Foreground Focal Loss for object detection

- FS Herrera, JM Saavedra

70. An Efficient Solution for Semantic Segmentation of Three Ground‐based Cloud Datasets

- Q Song, Z Cui, P Liu

71. Cell Nuclear Morphology Analysis Using 3D Shape Modeling, Machine Learning and Visual Analytics

- A Kalinin

72. DAugNet: Unsupervised, Multi-source, Multi-target, and Life-long Domain Adaptation for Semantic Segmentation of Satellite Images

- O Tasar, A Giros, Y Tarabalka, P Alliez

73. Deep Depth From Aberration Map

- M Kashiwagi, N Mishima

74. Contextual Pyramid Attention Network for Building Segmentation in Aerial Imagery

- C Sebastian, R Imbriaco, E Bondarev

75. A Novel Approach to Data Augmentation for Pavement Distress Segmentation

- D Mazzini, P Napoletano, F Piccoli, R Schettini

76. Augmentation-Based Object Detection for Winter Time Applications

- R Yagfarov, V Ostankovich

77. Automatic lesion boundary detection in dermoscopy

- G Kechyn

78. Visual Anomaly Detection For Automatic Quality Control

- F Piccoli

79. When Texture Matters: Texture-Focused Cnns Outperform General Data Augmentation and Pretraining in Oral Cancer Detection

- E Wetzer, J Gay, H Harlin, J Lindblad

80. Understanding the decisions of CNNs: an in-model approach

- I Rio-Torto, K Fernandes, LÃF Teixeira

81. Automatic phantom test pattern classification through transfer learning with deep neural networks

- RB Fricks, J Solomon, E Samei

82. Monitoring sugar crystallization with deep neural networks

- J Zhang, Y Meng, J Wu, J Qin, T Yao, S Yu

83. Flood detection with Sentinel-2 satellite images in crisis management systems

- A Moumtzidou, M Bakratsas, S Andreadis

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