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-to-robot pose estimation from a single image

- TE Lee, J Tremblay, T To, J Cheng

7. COVID-19 prediction and detection using deep learning

- M Alazab, A Awajan, A Mesleh

8. Camera model identification using convolutional neural networks

- A Kuzin, A Fattakhov, I Kibardin

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

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

10. Automated medical diagnosis of COVID-19 through EfficientNet convolutional neural network

- G Marques, D Agarwal, I de la Torre Díez

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

- SM Hasan, CA Linte

12. Deep convolutions for in-depth automated rock typing

- EE Baraboshkin, LS Ismailova, DM Orlov

13. Automatic salt deposits segmentation: A deep learning approach

- M Karchevskiy, I Ashrapov, L Kozinkin

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

- Y Babakhin, A Sanakoyeu, H Kitamura

15. Breast tumor cellularity assessment using deep neural networks

- A Rakhlin, A Tiulpin, AA Shvets

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

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

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

- Á Casado-García, C Domínguez

18. Severity Assessment and Progression Prediction of COVID-19 Patients based on the LesionEncoder Framework and Chest CT

- Y Feng, S Liu, Z Cheng, J Quiroz, P Chen, Q Lin

19. Pneumothorax Segmentation with Effective Conditioned Post-Processing in Chest X-Ray

- V GROZA, A KUZIN

20. 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

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

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

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

- SMK Hasan, CA Linte

23. Moiré pattern removal via attentive fractal network

- D Xu, Y Chu, Q Sun

24. Identifying melanoma images using efficientnet ensemble: Winning solution to the siim-isic melanoma classification challenge

- Q Ha, B Liu, F Liu

25. Semantic segmentation of smartphone wound images: Comparative analysis of AHRF and CNN-based approaches

- A Wagh, S Jain, A Mukherjee, E Agu

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

- I Ullah, P Chikontwe, SH Park

27. ImageNet Pre-trained CNNs for JPEG Steganalysis

- Y Yousfi, J Butora, E Khvedchenya

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

- W Wang, RA Solovyev, AL Stempkovsky

29. Multi-class brain tumor segmentation via multi-sequences mri mixture data preprocessing

- A Letyagin, S Golushko, M Amelin

30. Road Segmentation using U-Net architecture

- NYQ Abderrahim, S Abderrahim

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

- J Moosmann, DCF Wieland

32. Adapting Convolutional Neural Networks for Geographical Domain Shift

- P Ostyakov, SI Nikolenko

33. Deep Learning Methods for Screening Pulmonary Tuberculosis Using Chest X-rays

- C Dasanayaka, MB Dissanayake

34. Development and evaluation of deep learning–based segmentation of histologic structures in the kidney cortex with multiple histologic stains

- CP Jayapandian, Y Chen, AR Janowczyk, MB Palmer

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

- Q Liu, M Kampffmeyer, R Jenssen

36. Road Damage Detection and Classification with Detectron2 and Faster R-CNN

- V Pham, C Pham, T Dang

37. CRNNs for Urban Sound Tagging with spatiotemporal context

- A Arnault, N Riche

38. Not My Deepfake: Towards Plausible Deniability for Machine-Generated Media

- B Zhang, JP Zhou, I Shumailov, N Papernot

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

- O Tasar, Y Tarabalka, A Giros

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

- H Tang, A Ortis, S Battiato

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

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

42. Training CNNs in Presence of JPEG Compression: Multimedia Forensics vs Computer Vision

- S Mandelli, N Bonettini, P Bestagini

43. A modular region and text line layout analysis system

- B Kiessling

44. 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

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

- I Baran, O Kupyn, A Kravchenko

46. A Two-Stream Context-Aware ConvNet for Pavement Distress Detection

- R Lõuk, A Tepljakov, A Riid

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

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

48. Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural …

- M Burduja, RT Ionescu, N Verga

49. Fully automatic CNN-based segmentation of retinal bifurcations in 2D adaptive optics ophthalmoscopy images

- I Trimeche, F Rossant, I Bloch

50. A U-Net Based Approach for Automating Tribological Experiments

- B Staar, S Bayrak, D Paulkowski, M Freitag

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

- MA Kutlugün, Y Sirin

52. Impact of lung segmentation on the diagnosis and explanation of COVID-19 in chest X-ray images

- LO Teixeira, RM Pereira, D Bertolini, LS Oliveira

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

- O Baghirli, I Ibrahimli, T Mammadzada

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

- R Moghe, R Zanetti

55. Deep Learning object detection architectures in ADAS

- UO Etxabe, AG Basauri

56. Video Face Manipulation Detection Through Ensemble of CNNs

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

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

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

58. A weak supervision machine vision detection method based on artificial defect simulation

- C Li, Y Huang, H Li, X Zhang

59. Deep-learning based segmentation of challenging myelin sheaths

- T Le Couedic, R Caillon, F Rossant

60. Point Proposal based Instance Segmentation with Rectangular Masks for Robot Picking Task

- S Ito, S Kubota

61. Neural Mesh Refiner for 6-DoF Pose Estimation

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

62. Classification and understanding of cloud structures via satellite images with EfficientUNet

- T Ahmed, NHN Sabab

63. Speech Driven Talking Face Generation from a Single Image and an Emotion Condition

- SE Eskimez, Y Zhang, Z Duan

64. 2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge

- Y Gu, Y Pan, S Chen

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

- P Shved

66. Analysis of medical images using deep learning

- A Utegulov

67. An original framework for Wheat Head Detection using Deep, Semi-supervised and Ensemble Learning within Global Wheat Head Detection (GWHD) Dataset

- F Fourati, W Souidene, R Attia

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

- V Guryanova

69. Artificial Intelligence in Quantitative Ultrasound Imaging: A Review

- B Zhou, X Yang, T Liu

70. Embedded real-time inference in spiking neural networks for neuromorphic IoT vision sensors

- J Verecken, D Bol, C De Vleeschouwer

71. Segmentation model of the opacity regions in the chest X-rays of the Covid-19 patients in the us rural areas and the application to the disease severity

- H Tang, N Sun, Y Li

72. End-to-end Deep Learning Methods for Automated Damage Detection in Extreme Events at Various Scales

- Y Bai, H Sezen, A Yilmaz

73. Deep Learning for Regular Change Detection in Ukrainian Forest Ecosystem With Sentinel-2

- K Isaienkov, M Yushchuk, V Khramtsov

74. Data Preprocessing Via Compositions Multi-Channel MRI Images to Improve Brain Tumor Segmentation

- N Tolstokulakov, E Pavlovskiy

75. DCNN-based Screw Classification in Automated Disassembly Processes

- E Yildiz, F Wörgötter

76. Few-Shot Learning with Deep Neural Networks for Visual Quality Control: Evaluations on a Production Line

- N Yavari

77. Video and Sensor-Based Rope Pulling Detection in Sport Climbing

- I Ivanova, M Andrić, S Moaveninejad, A Janes

78. Differentiable Data Augmentation with Kornia

- J Shi, E Riba, D Mishkin, F Moreno

79. Estimating Displaced Populations from Overhead

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

80. Refinement network for unsupervised on the scene foreground segmentation

- M Pardàs Feliu, G Canet Tarrés

81. Machine Learning Algorithm Validation: From Essentials to Advanced Applications and Implications for Regulatory Certification and Deployment

- F Maleki, N Muthukrishnan, K Ovens

82. Efficient Palm-Line Segmentation with U-Net Context Fusion Module

- TP Van, ST Nguyen, LB Doan, NN Tran, TM Thanh

83. 车载探地雷达地下目标实时探测法

- 杨必胜，宗泽亮，陈驰，孙文鹿，米晓新，吴唯同

84. Multi-Label Contrastive Learning for Abstract Visual Reasoning

- M Małkiński, J Mańdziuk

85. Deep local directional embeddings para detección de objetos

- FE Souto Herrera

86. A Method for Automatic Tracking of Cell Nuclei With Weakly-Supervised Mitosis Detection in 2D Microscopy Image Sequences

- AY Kondratiev, H Yaginuma, Y Okada

87. Segmentation and Defect Classification of the Power Line Insulators: A Deep Learning-based Approach

- A Alahyari, A Hinneck, R Tariverdi, D Pozo

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

- LP Soares, HC Dias, CH Grohmann

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

- A Sheka, V Samun, T Chumarnaya

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

- S Varadarajan, S Kant, MM Srivastava

91. The Inclusive Images Competition

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

92. 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

93. Application of shared backbone DNNs in ADAS perception systems

- MG Lobanov, DL Sholomov

94. Αναγνώριση προσώπων με τεχνικές βαθιάς μηχανικής μάθησης

- Θ Κασσιώτης

95. Dermoscopic attributes classification using deep learning and multi-task learning

- I Saitov, T Polevaya, A Filchenkov

96. Image Stylization for Robust Features

- I Melekhov, GJ Brostow, J Kannala

97. Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts

- T Nickchen, S Heindorf, G Engels

98. Automatic Sorting of Dwarf Minke Whale Underwater Images

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

99. A Flatter Loss for Bias Mitigation in Cross-dataset Facial Age Estimation

- A Akbari, M Awais, ZH Feng, A Farooq

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

- FVM Perez

101. Two-Stream Convolutional Neural Network Based on Gradient Image for Aluminum Profile Surface Defects Classification and Recognition

- C Duan, T Zhang

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

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

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

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

104. DARWIN: A Highly Flexible Platform for Imaging Research in Radiology

- L Chang, W Zhuang, R Wu, S Feng, H Liu, J Yu

105. Return on Investment in Machine Learning: Crossing the Chasm between Academia and Business

- J Mizgajski, A Szymczak, M Morzy

106. Deep learning for retail product recognition: challenges and techniques

- Y Wei, S Tran, S Xu, B Kang, M Springer

107. Fiscal classification using convolutional neural network

- N Bindal, R Modi, BK Kaushik

108. CASS Studies

- HEB CASS

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

- LM Ellefsen

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

- FVM Perez

111. Fiche de confidentialité et de diffusion du mémoire

- O Non

112. Deepfake detection using capsule networks with long short-term memory networks

- A Mehra

113. О важности аугментации данных при машинном обучении в задачах обработки изображений в условиях дефицита данных

- НА Андриянов, ДА Андриянов

114. Image-based high-throughput detection and phenotype evaluation method for multiple lettuce varieties

- J Du, X Lu, J Fan, Y Qin, X Yang

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

- AM MORA

116. SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation

- Q Liu, M Kampffmeyer, R Jenssen

117. DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation

- Y Zeng, H Qiu, S Guo, T Zhang, M Qiu

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

- A Wagh

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

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

120. Generative augmentation to improve lung nodules detection in resource-limited settings

- NF Gusarova, AA Lobantsev, AS Vatian

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

- AY Wagh

122. Side-Scan Sonar Image Synthesis Based on Generative Adversarial Network for Images in Multiple Frequencies

- Y Jiang, B Ku, W Kim, H Ko

123. Targeting the zebrafish eye using deep learning-based image segmentation

- J Holmberg

124. Urban Sound Tagging using Convolutional Neural Networks

- S Adapa

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

- A Zhuchkov, D Prokhorov, V Gusev

126. 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

127. Deep Learning-based Object Understanding for Robotic Manipulation

- JS Moon, HJ Jo, JB Song

128. Use of Images Augmentation and Implementation of Doubly Stochastic Models for Improving Accuracy of Recognition Algorithms Based on Convolutional Neural …

- VE Dementyiev, NA Andriyanov

129. Encoder-Recurrent Decoder Network for Single Image Dehazing

- A Dang, TH Vu, JC Wang

130. Application of neural networks to image recognition of wheat rust diseases

- M Genaev, S Ekaterina

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

- A Kozlov

132. NoGAN: Deblurring Images without Adversarial Training

- R Vei

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

- H Chen, C Lian, L Wang

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

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

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

- M Scott, J Plested

136. Simulation to reality: Study and demonstration of domain adaptation techniques applied to Reinforcement and Supervised learning algorithms

- P Miralles Roure

137. AGUnet: Annotation-guided U-net for fast one-shot video object segmentation

- Y Yin, D Xu, X Wang, L Zhang

138. Comparison of neural network architectures for segmentation of the left ventricle on EchoCG images

- VS Samun, AS Sheka, TV Chumarnaya

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

- FS Herrera, JM Saavedra

140. A Deep Learning Approach to Hazard Detection for Autonomous Lunar Landing

- R Moghe, R Zanetti

141. Rubik's Cube layout construction and validation algorithm

- B Borkivskyi

142. On the Accuracy of CRNNs for Line-Based OCR: A Multi-Parameter Evaluation

- B Liebl, M Burghardt

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

- Q Song, Z Cui, P Liu

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

- A Kalinin

145. Técnicas de aumento de datos para imágenes aéreas y evaluación de rendimiento en modelos de deep learning

- CCG Sarasa, JDO Pabón

146. Ring artifacts segmentation on microtomographic images by convolutional neural networks

- A Kornilov, I Safonov

147. 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

148. Deep Depth From Aberration Map

- M Kashiwagi, N Mishima

149. SpheroidJ: An Open-Source Set of Tools for Spheroid Segmentation

- D Lacalle, HA Castro-Abril, T Randelovic

150. Variational Beam Search for Online Learning with Distribution Shifts

- A Li, A Boyd, P Smyth, S Mandt

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

- C Sebastian, R Imbriaco, E Bondarev

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

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

153. Augmentation-Based Object Detection for Winter Time Applications

- R Yagfarov, V Ostankovich

154. Refinement Network for unsupervised on the scene Foreground Segmentation

- M Pardàs, G Canet

155. Automatic lesion boundary detection in dermoscopy

- G Kechyn

156. Training Strategies and Data Augmentations in CNN-based DeepFake Video Detection

- L Bondi, ED Cannas, P Bestagini, S Tubaro

157. Visual Anomaly Detection For Automatic Quality Control

- F Piccoli

158. Deep Learning-based Four-region Lung Segmentation in Chest Radiography for COVID-19 Diagnosis

- YG Kim, K Kim, D Wu, H Ren, WY Tak, SY Park

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

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

160. Urban Sound Classification: striving towards a fair comparison

- A Arnault, B Hanssens, N Riche

161. An Experimental Study of Semantic Continuity for Deep Learning Models

- S Wu, J Sang, X Zhao, L Chen

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

- I Rio-Torto, K Fernandes, LÃF Teixeira

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

- RB Fricks, J Solomon, E Samei

164. Проблемы детектирования объекта на изображении в задачах глубокого обучения в области компьютерного зрения на основе свёрточных …

- СВ Кравченко, АВ Алексеев, ЮА Орлова

165. Monitoring sugar crystallization with deep neural networks

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

166. Self Supervised Learning for Object Localisation in 3D Tomographic Images

- Y Zharov, A Ershov, T Baumbach

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

- A Moumtzidou, M Bakratsas, S Andreadis

168. Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering

- A Riabi, T Scialom, R Keraron, B Sagot

169. Faster R-CNN model learning on synthetic images

- B Łach, E Łukasik

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