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Albumentations is widely used in research areas related to computer vision and deep learning. If you find this library useful for your research, please consider citing Albumentations: Fast and Flexible Image Augmentations: 
@Article{info11020125,
    AUTHOR = {Buslaev, Alexander and Iglovikov, Vladimir I. and Khvedchenya, Eugene and Parinov, Alex and Druzhinin, Mikhail and Kalinin, Alexandr A.},
    TITLE = {Albumentations: Fast and Flexible Image Augmentations},
    JOURNAL = {Information},
    VOLUME = {11},
    YEAR = {2020},
    NUMBER = {2},
    ARTICLE-NUMBER = {125},
    URL = {https://www.mdpi.com/2078-2489/11/2/125},
    ISSN = {2078-2489},
    DOI = {10.3390/info11020125}
}

List of papers that cite Albumentations

1. Automatic instrument segmentation in robot-assisted surgery using deep learning
- AA Shvets, A Rakhlin, AA Kalinin
2. AutoML: A Survey of the State-of-the-Art
- X He, K Zhao, X Chu
3. Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better
- O Kupyn, T Martyniuk, J Wu
4. Angiodysplasia detection and localization using deep convolutional neural networks
- AA Shvets, VI Iglovikov, A Rakhlin
5. Self-supervised learning for dense depth estimation in monocular endoscopy
- X Liu, A Sinha, M Unberath, M Ishii, GD Hager
6. Transformation-consistent self-ensembling model for semisupervised medical image segmentation
- X Li, L Yu, H Chen, CW Fu, L Xing
7. Deep convolutions for in-depth automated rock typing
- EE Baraboshkin, LS Ismailova, DM Orlov
8. U-NetPlus: a modified encoder-decoder U-Net architecture for semantic and instance segmentation of surgical instrument
- SM Hasan, CA Linte
9. Semi-supervised segmentation of salt bodies in seismic images using an ensemble of convolutional neural networks
- Y Babakhin, A Sanakoyeu, H Kitamura
10. Video face manipulation detection through ensemble of cnns
- N Bonettini, ED Cannas, S Mandelli, L Bondi
11. Automated medical diagnosis of COVID-19 through EfficientNet convolutional neural network
- G Marques, D Agarwal, I de la Torre Díez
12. Automatic salt deposits segmentation: A deep learning approach
- M Karchevskiy, I Ashrapov, L Kozinkin
13. COVID-19 prediction and detection using deep learning
- M Alazab, A Awajan, A Mesleh, A Abraham
14. Camera model identification using convolutional neural networks
- A Kuzin, A Fattakhov, I Kibardin
15. End-to-end learning for semiquantitative rating of covid-19 severity on chest x-rays
- A Signoroni, M Savardi, S Benini, N Adami
16. Camera-to-robot pose estimation from a single image
- TE Lee, J Tremblay, T To, J Cheng
17. CLoDSA: a tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks
- Á Casado-García, C Domínguez
18. Urban sound tagging using convolutional neural networks
- S Adapa
19. 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
20. Breast tumor cellularity assessment using deep neural networks
- A Rakhlin, A Tiulpin, AA Shvets
21. General purpose (GenP) bioimage ensemble of handcrafted and learned features with data augmentation
- L Nanni, S Brahnam, S Ghidoni, G Maguolo
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. A framework for knowing who is doing what in aerial surveillance videos
- F Yang, S Sakti, Y Wu, S Nakamura
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. 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
27. The effects of augmented training dataset on performance of convolutional neural networks in face recognition system
- MA Kutlugün, Y Sirin
28. The Inclusive Images Competition
- J Atwood, Y Halpern, P Baljekar, E Breck
29. Moiré pattern removal via attentive fractal network
- D Xu, Y Chu, Q Sun
30. 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
31. EasyAug: An automatic textual data augmentation platform for classification tasks
- S Qiu, B Xu, J Zhang, Y Wang, X Shen
32. ImageNet Pre-trained CNNs for JPEG Steganalysis
- Y Yousfi, J Butora, E Khvedchenya
33. Pneumothorax Segmentation with Effective Conditioned Post-Processing in Chest X-Ray
- V GROZA, A KUZIN
34. Adapting Convolutional Neural Networks for Geographical Domain Shift
- P Ostyakov, SI Nikolenko
35. Online Augmentation for Quality Improvement of Neural Networks for Classification of Single-Channel Electrocardiograms
- V Guryanova
36. Deep learning with conformal prediction for hierarchical analysis of large-scale whole-slide tissue images
- H Wieslander, PJ Harrison, G Skogberg
37. Identifying melanoma images using efficientnet ensemble: Winning solution to the siim-isic melanoma classification challenge
- Q Ha, B Liu, F Liu
38. Weighted Ensemble Object Detection with Optimized Coefficients for Remote Sensing Images
- A Körez, N Barışçı, A Çetin, U Ergün
39. The Impact of Padding on Image Classification by Using Pre-trained Convolutional Neural Networks
- H Tang, A Ortis, S Battiato
40. Semantic segmentation of smartphone wound images: Comparative analysis of AHRF and CNN-based approaches
- A Wagh, S Jain, A Mukherjee, E Agu
41. Real-time tracking of guidewire robot tips using deep convolutional neural networks on successive localized frames
- I Ullah, P Chikontwe, SH Park
42. 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
43. Deep Depth From Aberration Map
- M Kashiwagi, N Mishima
44. A novel approach to data augmentation for pavement distress segmentation
- D Mazzini, P Napoletano, F Piccoli, R Schettini
45. Monitoring sugar crystallization with deep neural networks
- J Zhang, Y Meng, J Wu, J Qin, T Yao, S Yu
46. 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
47. Retinopathy diagnosis using semi-supervised multi-channel generative adversarial network
- Y Xie, Q Wan, G Chen, Y Xu, B Lei
48. Method for Whale Re-identification Based on Siamese Nets and Adversarial Training
- W Wang, RA Solovyev, AL Stempkovsky
49. Multi-class brain tumor segmentation via multi-sequences mri mixture data preprocessing
- A Letyagin, S Golushko, M Amelin
50. Road Segmentation using U-Net architecture
- NYQ Abderrahim, S Abderrahim
51. A load frame for in situ tomography at PETRA III
- J Moosmann, DCF Wieland
52. Deep Learning Methods for Screening Pulmonary Tuberculosis Using Chest X-rays
- C Dasanayaka, MB Dissanayake
53. Segmentation of the Left Ventricle on EchoCG Images Using MultiResUnet
- A Sheka, V Samun, T Chumarnaya
54. Benchmark for generic product detection: a strong baseline for dense object detection
- S Varadarajan, S Kant, MM Srivastava
55. Road Damage Detection and Classification with Detectron2 and Faster R-CNN
- V Pham, C Pham, T Dang
56. Automatic sorting of dwarf Minke whale underwater images
- DA Konovalov, N Swinhoe, DB Efremova, RA Birtles
57. Data Preprocessing via Multi-sequences MRI Mixture to Improve Brain Tumor Segmentation
- V Groza, B Tuchinov, E Pavlovskiy, E Amelina
58. CRNNs for Urban Sound Tagging with spatiotemporal context
- A Arnault, N Riche
59. Not My Deepfake: Towards Plausible Deniability for Machine-Generated Media
- B Zhang, JP Zhou, I Shumailov, N Papernot
60. Benchmark for Generic Product Detection: A Low Data Baseline for Dense Object Detection
- S Varadarajan, S Kant, MM Srivastava
61. Challenges in the deep learning-based semantic segmentation of benthic communities from Ortho-images
- G Pavoni, M Corsini, N Pedersen, V Petrovic
62. Endoscopy Artefact Detection and Segmentation using Deep Convolutional Neural Network.
- H Chen, C Lian, L Wang
63. Training CNNs in Presence of JPEG Compression: Multimedia Forensics vs Computer Vision
- S Mandelli, N Bonettini, P Bestagini
64. A modular region and text line layout analysis system
- B Kiessling
65. Deep Learning Predicts HPV Association in Oropharyngeal Squamous Cell Carcinomas and Identifies Patients with a Favorable Prognosis Using Regular H&E Stains
- S Klein, A Quaas, J Quantius, H Löser, J Meinel
66. DLDENet: Deep Local Directional Embeddings with Increased Foreground Focal Loss for object detection
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67. An Efficient Solution for Semantic Segmentation of Three Ground‐based Cloud Datasets
- Q Song, Z Cui, P Liu
68. Safe augmentation: Learning task-specific transformations from data
- I Baran, O Kupyn, A Kravchenko
69. A Two-Stream Context-Aware ConvNet for Pavement Distress Detection
- R Lõuk, A Tepljakov, A Riid
70. Augmentation-based object detection for winter time applications
- R Yagfarov, V Ostankovich
71. When texture matters: texture-focused CNNs outperform general data augmentation and pretraining in oral cancer detection
- E Wetzer, J Gay, H Harlin, J Lindblad
72. 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
73. Fully automatic CNN-based segmentation of retinal bifurcations in 2D adaptive optics ophthalmoscopy images
- I Trimeche, F Rossant, I Bloch
74. A U-Net Based Approach for Automating Tribological Experiments
- B Staar, S Bayrak, D Paulkowski, M Freitag
75. Greenhouse Segmentation on High-Resolution Optical Satellite Imagery using Deep Learning Techniques
- O Baghirli, I Ibrahimli, T Mammadzada
76. Artificial Intelligence based identification of Total Knee Arthroplasty Implants
- S Ghose, S Datta, V Batta, C Malathy
77. On-line hazard detection algorithm for precision lunar landing using semantic segmentation
- R Moghe, R Zanetti
78. A CNN-based length-aware cascade road damage detection approach
- H Xu, B Chen, J Qin
79. Deep Learning object detection architectures in ADAS
- UO Etxabe, AG Basauri
80. Digital Peter: Dataset, Competition and Handwriting Recognition Methods
- M Potanin, D Dimitrov, A Shonenkov, V Bataev
81. A weak supervision machine vision detection method based on artificial defect simulation
- C Li, Y Huang, H Li, X Zhang
82. Deep-learning based segmentation of challenging myelin sheaths
- T Le Couedic, R Caillon, F Rossant
83. Point Proposal based Instance Segmentation with Rectangular Masks for Robot Picking Task
- S Ito, S Kubota
84. Neural Mesh Refiner for 6-DoF Pose Estimation
- D Wu, Y Chen, X Qi, Y Jian, W Chen, R Xiao
85. Classification and understanding of cloud structures via satellite images with EfficientUNet
- T Ahmed, NHN Sabab
86. Speech Driven Talking Face Generation from a Single Image and an Emotion Condition
- SE Eskimez, Y Zhang, Z Duan
87. The Study of Improving the Accuracy of Convolutional Neural Networks in Face Recognition Tasks
- N Andriyanov, V Dementev
88. ИСПОЛЬЗОВАНИЕ АУГМЕНТАЦИИ ИЗОБРАЖЕНИЙ И РЕАЛИЗАЦИЯ ДВАЖДЫ СТОХАСТИЧЕСКИХ МОДЕЛЕЙ ДЛЯ ПОВЫШЕНИЯ ЭФФЕКТИВНОСТИ …
- ВЕ Дементьев, НА Андриянов
89. 2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge
- Y Gu, Y Pan, S Chen
90. Unsupervised Domain Adaptation from Axial toShort-Axis Multi-Slice Cardiac MR Images byIncorporating Pretrained Task Networks
- S Koehler, T Hussain, Z Blair, T Huffaker
91. A Battery-Powered Friend: Towards Embedded Emotion Recognition
- P Shved
92. Οπτική αναγνώριση αντικειμένων σε μεγάλες βάσεις δεδομένων
- Α Κωστόπουλος
93. Single-shot cuboids: Geodesics-based end-to-end Manhattan aligned layout estimation from spherical panoramas
- N Zioulis, F Alvarez, D Zarpalas, P Daras
94. Analysis of medical images using deep learning
- A Utegulov
95. 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
96. Artificial Intelligence in Quantitative Ultrasound Imaging: A Review
- B Zhou, X Yang, T Liu
97. Embedded real-time inference in spiking neural networks for neuromorphic IoT vision sensors
- J Verecken, D Bol, C De Vleeschouwer
98. 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
99. End-to-end Deep Learning Methods for Automated Damage Detection in Extreme Events at Various Scales
- Y Bai, H Sezen, A Yilmaz
100. Deep Learning for Regular Change Detection in Ukrainian Forest Ecosystem With Sentinel-2
- K Isaienkov, M Yushchuk, V Khramtsov
101. Arrow R-CNN for handwritten diagram recognition
- B Schäfer, M Keuper, H Stuckenschmidt
102. Data Preprocessing Via Compositions Multi-Channel MRI Images to Improve Brain Tumor Segmentation
- N Tolstokulakov, E Pavlovskiy
103. Feature-based image registration in structured light endoscopy
- AM Kist, J Zilker, M Döllinger, M Semmler
104. DCNN-based Screw Classification in Automated Disassembly Processes
- E Yildiz, F Wörgötter
105. Few-Shot Learning with Deep Neural Networks for Visual Quality Control: Evaluations on a Production Line
- N Yavari
106. Principled Ultrasound Data Augmentation for Classification of Standard Planes
- LH Lee, Y Gao, JA Noble
107. Video and Sensor-Based Rope Pulling Detection in Sport Climbing
- I Ivanova, M Andrić, S Moaveninejad, A Janes
108. Differentiable Data Augmentation with Kornia
- J Shi, E Riba, D Mishkin, F Moreno
109. Estimating Displaced Populations from Overhead
- A Hadzic, G Christie, J Freeman, A Dismer
110. Refinement network for unsupervised on the scene foreground segmentation
- M Pardàs Feliu, G Canet Tarrés
111. Machine Learning Algorithm Validation: From Essentials to Advanced Applications and Implications for Regulatory Certification and Deployment
- F Maleki, N Muthukrishnan, K Ovens
112. Efficient Palm-Line Segmentation with U-Net Context Fusion Module
- TP Van, ST Nguyen, LB Doan, NN Tran
113. Learning Accurate Dense Correspondences and When to Trust Them
- P Truong, M Danelljan, L Van Gool
114. 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
115. Multi-Label Contrastive Learning for Abstract Visual Reasoning
- M Małkiński, J Mańdziuk
116. Deep local directional embeddings para detección de objetos
- FE Souto Herrera
117. A Method for Automatic Tracking of Cell Nuclei With Weakly-Supervised Mitosis Detection in 2D Microscopy Image Sequences
- AY Kondratiev, H Yaginuma, Y Okada
118. Segmentation and Defect Classification of the Power Line Insulators: A Deep Learning-based Approach
- A Alahyari, A Hinneck, R Tariverdi, D Pozo
119. FlashNeuron: SSD-Enabled Large-Batch Training of Very Deep Neural Networks
- J Bae, J Lee, Y Jin, S Son, S Kim, H Jang
120. Landslide Segmentation with U-Net: Evaluating Different Sampling Methods and Patch Sizes
- LP Soares, HC Dias, CH Grohmann
121. Application of shared backbone DNNs in ADAS perception systems
- MG Lobanov, DL Sholomov
122. Variational Beam Search for Novelty Detection
- A Li, A Boyd, P Smyth, S Mandt
123. Αναγνώριση προσώπων με τεχνικές βαθιάς μηχανικής μάθησης
- Θ Κασσιώτης
124. Dermoscopic attributes classification using deep learning and multi-task learning
- I Saitov, T Polevaya, A Filchenkov
125. Image Stylization for Robust Features
- I Melekhov, GJ Brostow, J Kannala
126. Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts
- T Nickchen, S Heindorf
127. CNN and Deep Sets for End-to-End Whole Slide Image Representation Learning
- S Hemati, S Kalra, C Meaney, M Babaie, A Ghodsi
128. A Flatter Loss for Bias Mitigation in Cross-dataset Facial Age Estimation
- A Akbari, M Awais, ZH Feng, A Farooq
129. Deep learning for skin lesion classification: augment, train, and ensemble= Aprendizado profundo para classificação de lesões de pele: aumento, treino e conjunto
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130. Two-Stream Convolutional Neural Network Based on Gradient Image for Aluminum Profile Surface Defects Classification and Recognition
- C Duan, T Zhang
131. Physical Cue based Depth-Sensing by Color Coding with Deaberration Network
- N Mishima, T Kozakaya, A Moriya, R Okada
132. DARWIN: A Highly Flexible Platform for Imaging Research in Radiology
- L Chang, W Zhuang, R Wu, S Feng, H Liu, J Yu
133. Return on Investment in Machine Learning: Crossing the Chasm between Academia and Business
- J Mizgajski, A Szymczak, M Morzy
134. Deep learning for retail product recognition: challenges and techniques
- Y Wei, S Tran, S Xu, B Kang, M Springer
135. Fiscal classification using convolutional neural network
- N Bindal, R Modi, BK Kaushik
136. 机器视觉应用中的图像数据增广综述
- 林成创， 单纯， 赵淦森
137. CASS Studies
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138. Cloud Recognition and Masking of Earth Observation Imagery-An Optimized approach for Automatic Labeling of Sentinel-2 Imagery for Object Detection
- LM Ellefsen
139. Convolutional Neural Network for Drowsiness Detection Using EEG Signals
- S Chaabene, B Bouaziz, A Boudaya, A Hökelmann
140. Deep Learning for Skin Lesion Classification: Augment, Train, and Ensemble
- FVM Perez
141. Fiche de confidentialité et de diffusion du mémoire
- O Non
142. Deepfake detection using capsule networks with long short-term memory networks
- A Mehra
143. О важности аугментации данных при машинном обучении в задачах обработки изображений в условиях дефицита данных
- НА Андриянов, ДА Андриянов
144. Image-based high-throughput detection and phenotype evaluation method for multiple lettuce varieties
- J Du, X Lu, J Fan, Y Qin, X Yang
145. Automation of Kidney Perfusion Analysis from Dynamic Phase-Contrast MRI using Deep Learning
- AM MORA
146. Danish Fungi 2020--Not Just Another Image Recognition Dataset
- L Picek, M Šulc, J Matas, J Heilmann-Clausen
147. SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation
- Q Liu, M Kampffmeyer, R Jenssen
148. DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation
- Y Zeng, H Qiu, S Guo, T Zhang, M Qiu
149. Underwater Object Detection With Mixed Attention Mechanism And Multi-Enhancement Strategy
- W Chen, B Fan
150. Semantic Segmentation of Smartphone Wound Images: Comparative Analysis of AHRF and CNN-Based Approaches WPI Technical Report WPI-CS-TR-19-02
- A Wagh
151. Generative augmentation to improve lung nodules detection in resource-limited settings
- NF Gusarova, AA Lobantsev, AS Vatian
152. A Deep 3D Object Pose Estimation Framework for Robots with RGB-D Sensors
- AY Wagh
153. Synthesize and Segment: Towards Improved Catheter Segmentation via Adversarial Augmentation
- I Ullah, P Chikontwe, H Choi, CH Yoon, SH Park
154. Side-Scan Sonar Image Synthesis Based on Generative Adversarial Network for Images in Multiple Frequencies
- Y Jiang, B Ku, W Kim, H Ko
155. MANet: A Two-stage Deep Learning Method for Classification of COVID-19 from Chest X-ray Images
- Y Xu, HK Lam, G Jia
156. Targeting the zebrafish eye using deep learning-based image segmentation
- J Holmberg
157. Seismic Interpretation of Partially Labeled 3D Cube with Neural Networks
- A Zhuchkov, D Prokhorov, V Gusev
158. 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
159. Classification of Chest X-ray Images Using Machine Learning Techniques
- A Ahmed, G Tharwat, B Bouallegue, M Khattab
160. Deep Learning-based Object Understanding for Robotic Manipulation
- JS Moon, HJ Jo, JB Song
161. Use of Images Augmentation and Implementation of Doubly Stochastic Models for Improving Accuracy of Recognition Algorithms Based on Convolutional Neural …
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162. Encoder-Recurrent Decoder Network for Single Image Dehazing
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163. Application of neural networks to image recognition of wheat rust diseases
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164. 3DeepM: An Ad Hoc Architecture Based on Deep Learning Methods for Multispectral Image Classification. Remote Sens. 2021, 13, 729
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165. Working with scale: 2nd place solution to Product Detection in Densely Packed Scenes [Technical Report]
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166. NoGAN: Deblurring Images without Adversarial Training
- R Vei
167. MaskHunter: real-time object detection of face masks during the COVID-19 pandemic
- Z Cao, M Shao, L Xu, S Mu, H Qu
168. SEGMENTATION OF CLOUD PATTERNS FROM SATELLITE IMAGES TO IMPROVE CLIMATE MODELS
- K Vishnyakov, M Organokov
169. GAN-SMOTE: A Generative Adversarial Network approach to Synthetic Minority Oversampling for One-Hot Encoded Data
- M Scott, J Plested
170. Robust Skin Disease Classification by Distilling Deep Neural Network Ensemble for the Mobile Diagnosis of Herpes Zoster
- S Back, S Lee, S Shin, Y Yu, T Yuk, S Jong
171. Simulation to reality: Study and demonstration of domain adaptation techniques applied to Reinforcement and Supervised learning algorithms
- P Miralles Roure
172. AGUnet: Annotation-guided U-net for fast one-shot video object segmentation
- Y Yin, D Xu, X Wang, L Zhang
173. CrackWeb: A modified U-Net based segmentation architecture for crack detection
- S Ghosh, S Singh, A Maity
174. Detecting subsurface drainage pipes using a fully convolutional network with optical images
- H Song, DK Woo, Q Yan
175. Comparison of neural network architectures for segmentation of the left ventricle on EchoCG images
- VS Samun, AS Sheka, TV Chumarnaya
176. MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels
- P Gómez, G Meoni
177. A Deep learning approach to Hazard detection for Autonomous Lunar landing
- R Moghe, R Zanetti
178. Rubik's Cube layout construction and validation algorithm
- B Borkivskyi
179. Annotation quality vs. quantity for deep-learned medical image segmentation
- T Wesemeyer, ML Jauer
180. On the Accuracy of CRNNs for Line-Based OCR: A Multi-Parameter Evaluation
- B Liebl, M Burghardt
181. Cell Nuclear Morphology Analysis Using 3D Shape Modeling, Machine Learning and Visual Analytics
- A Kalinin
182. Técnicas de aumento de datos para imágenes aéreas y evaluación de rendimiento en modelos de deep learning
- CCG Sarasa, JDO Pabón
183. Ring artifacts segmentation on microtomographic images by convolutional neural networks
- A Kornilov, I Safonov
184. DAugNet: Unsupervised, Multisource, Multitarget, and Life-Long Domain Adaptation for Semantic Segmentation of Satellite Images
- O Tasar, A Giros, Y Tarabalka, P Alliez
185. IIE-NLP-Eyas at SemEval-2021 Task 4: Enhancing PLM for ReCAM with Special Tokens, Re-Ranking, Siamese Encoders and Back Translation
- Y Xie, L Xing, W Peng, Y Hu
186. SpheroidJ: An Open-Source Set of Tools for Spheroid Segmentation
- D Lacalle, HA Castro-Abril, T Randelovic
187. Variational Beam Search for Online Learning with Distribution Shifts
- A Li, A Boyd, P Smyth, S Mandt
188. Contextual Pyramid Attention Network for Building Segmentation in Aerial Imagery
- C Sebastian, R Imbriaco, E Bondarev
189. HISTOPATHOLOGY LEARNING DATASET AUGMENTATION: A HYBRID APPROACH
- R HAMDI, C Bouvier, T Delzescaux, C Clouchoux
190. Refinement Network for unsupervised on the scene Foreground Segmentation
- M Pardàs, G Canet
191. Automatic lesion boundary detection in dermoscopy
- G Kechyn
192. Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
- MN Rizve, S Khan, FS Khan, M Shah
193. Training Strategies and Data Augmentations in CNN-based DeepFake Video Detection
- L Bondi, ED Cannas, P Bestagini, S Tubaro
194. 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
195. Urban Sound Classification: striving towards a fair comparison
- A Arnault, B Hanssens, N Riche
196. ИСПОЛЬЗОВАНИЕ АУГМЕНТАЦИИ ИЗОБРАЖЕНИЙ СОВМЕСТНО С РЕАЛИЗАЦИЕЙ ДВАЖДЫ СТОХАСТИЧЕСКОЙ МОДЕЛИ ДЛЯ УЛУЧШЕНИЯ КАЧЕСТВА …
- НА Андриянов, ВЕ Дементьев
197. An Experimental Study of Semantic Continuity for Deep Learning Models
- S Wu, J Sang, X Zhao, L Chen
198. Understanding the decisions of CNNs: An in-model approach
- I Rio-Torto, K Fernandes, LF Teixeira
199. Automatic phantom test pattern classification through transfer learning with deep neural networks
- RB Fricks, J Solomon, E Samei
200. Проблемы детектирования объекта на изображении в задачах глубокого обучения в области компьютерного зрения на основе свёрточных …
- СВ Кравченко, АВ Алексеев, ЮА Орлова
201. Semi-supervised Learning with a Teacher-Student Paradigm for Histopathology Classification: A Resource to Face Data Heterogeneity and Lack of Local …
- N Marini, S Otálora, H Müller
202. Self Supervised Learning for Object Localisation in 3D Tomographic Images
- Y Zharov, A Ershov, T Baumbach
203. Flood detection with Sentinel-2 satellite images in crisis management systems
- A Moumtzidou, M Bakratsas, S Andreadis
204. Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering
- A Riabi, T Scialom, R Keraron, B Sagot
205. 3DeepM: An Ad Hoc Architecture Based on Deep Learning Methods for Multispectral Image Classification
- PJ Navarro, L Miller, A Gila-Navarro, MV Díaz-Galián
206. Faster R-CNN model learning on synthetic images
- B Łach, E Łukasik

Machine learning competitions

Deepfake Detection Challenge
solution
code
1st place
Platform: Kaggle
Deepfake Detection Challenge
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code
3rd place
Platform: Kaggle
Deepfake Detection Challenge
solution
code
5th place
Platform: Kaggle
Deepfake Detection Challenge
solution
code
12th place
Platform: Kaggle
Prostate cANcer graDe Assessment (PANDA) Challenge
solution
2nd place
Platform: Kaggle
Prostate cANcer graDe Assessment (PANDA) Challenge
solution
code
3rd place
Platform: Kaggle
Prostate cANcer graDe Assessment (PANDA) Challenge
solution
code
6th place
Platform: Kaggle
Prostate cANcer graDe Assessment (PANDA) Challenge
solution
code
8th place
Platform: Kaggle
Prostate cANcer graDe Assessment (PANDA) Challenge
solution
11th place
Platform: Kaggle
Peking University/Baidu - Autonomous Driving
solution
2nd place
Platform: Kaggle
Peking University/Baidu - Autonomous Driving
solution
code
5th place
Platform: Kaggle
Peking University/Baidu - Autonomous Driving
solution
code
7th place
Platform: Kaggle
Bengali.AI Handwritten Grapheme Classification
solution
1st place
Platform: Kaggle
Bengali.AI Handwritten Grapheme Classification
solution
8th place
Platform: Kaggle
Bengali.AI Handwritten Grapheme Classification
solution
code
10th place
Platform: Kaggle
RSNA Intracranial Hemorrhage Detection
solution
code
1st place
Platform: Kaggle
RSNA Intracranial Hemorrhage Detection
solution
code
2nd place
Platform: Kaggle
RSNA Intracranial Hemorrhage Detection
solution
code
4th place
Platform: Kaggle
RSNA Intracranial Hemorrhage Detection
solution
code
8th place
Platform: Kaggle
RSNA Intracranial Hemorrhage Detection
solution
code
10th place
Platform: Kaggle
RSNA Intracranial Hemorrhage Detection
solution
code
11th place
Platform: Kaggle
Severstal: Steel Defect Detection
solution
code
1st place
Platform: Kaggle
Severstal: Steel Defect Detection
solution
10th place
Platform: Kaggle
Severstal: Steel Defect Detection
solution
12th place
Platform: Kaggle
Severstal: Steel Defect Detection
solution
14th place
Platform: Kaggle
Understanding Clouds from Satellite Images
solution
code
1st place
Platform: Kaggle
Understanding Clouds from Satellite Images
solution
2nd place
Platform: Kaggle
Understanding Clouds from Satellite Images
solution
5th place
Platform: Kaggle
Understanding Clouds from Satellite Images
solution
10th place
Platform: Kaggle
Kuzushiji Recognition
solution
code
2nd place
Platform: Kaggle
Kuzushiji Recognition
solution
code
4th place
Platform: Kaggle
Kuzushiji Recognition
solution
code
5th place
Platform: Kaggle
Kuzushiji Recognition
solution
code
8th place
Platform: Kaggle
Kuzushiji Recognition
solution
code
9th place
Platform: Kaggle
APTOS 2019 Blindness Detection
solution
2nd place
Platform: Kaggle
APTOS 2019 Blindness Detection
solution
code
7th place
Platform: Kaggle
APTOS 2019 Blindness Detection
solution
9th place
Platform: Kaggle
Recursion Cellular Image Classification
solution
code
4th place
Platform: Kaggle
Recursion Cellular Image Classification
solution
7th place
Platform: Kaggle
Open Cities AI Challenge: Segmenting Buildings for Disaster Resilience
code
1st place
Platform: DrivenData
Urban Sound Tagging
code
1st place
Platform: DCASE
xView2 Damage Assessment Challenge
code
3rd place
Platform: xView2
Carvana Image Masking Challenge
solution
1st place
Platform: Kaggle
Data Science Bowl 2018
solution
1st place
Platform: Kaggle
Humpback Whale Identification
blog post
code
5th place
Platform: Kaggle
TGS Salt Identification Challenge
solution
code
pre-print
1st place
Platform: Kaggle
TGS Salt Identification Challenge
blog post
code
pre-print
27th place
Platform: Kaggle
APTOS 2019 Blindness Detection
solution
code
7th place
Platform: Kaggle
APTOS 2019 Blindness Detection
solution
code
76th place
Platform: Kaggle
SIIM-ACR Pneumothorax Segmentation
solution
code
video
presentation
1st place
Platform: Kaggle
SIIM-ACR Pneumothorax Segmentation
solution
code
4th place
Platform: Kaggle
SIIM-ACR Pneumothorax Segmentation
solution
33rd place
Platform: Kaggle
SIIM-ACR Pneumothorax Segmentation
code and solution
50th place
Platform: Kaggle
iMaterialist (Fashion) 2019 at FGVC6
solution
code
1st place
Platform: Kaggle
Google Landmark Recognition 2019
solution
code
20th place
Platform: Kaggle
Inclusive Images Challenge
solution
3rd place
Platform: Kaggle
Airbus Ship Detection Challenge
paper
30th place
Platform: Kaggle
Neptune - Facial Detection Marathon Match
solution
2nd place
Platform: Topcoder
Neptune - Facial Re-Identification Marathon Match
solution
2nd place
Platform: Topcoder
SpaceNet Challenge Round 4: Off-Nadir Buildings
solution
3rd place
Platform: Topcoder
DeepGlobe: Road Extraction
paper
2nd place
Platform: CVPR
Deepglobe: Building detection
paper
2nd place
Platform: CVPR
Deepglobe: Land Cover Classification
paper
3rd place
Platform: CVPR
Robotic Instrument Segmentation
paper
pre-print from organizers
1st place
Platform: MICCAI
GIANA: Angiodysplasia localization
paper
1st place
Platform: MICCAI

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