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. 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

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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

- FS Herrera, JM Saavedra

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

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

81. Deep-learning based segmentation of challenging myelin sheaths

- T Le Couedic, R Caillon, F Rossant

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

- S Ito, S Kubota

83. Neural Mesh Refiner for 6-DoF Pose Estimation

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

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

- T Ahmed, NHN Sabab

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

- SE Eskimez, Y Zhang, Z Duan

86. ИСПОЛЬЗОВАНИЕ АУГМЕНТАЦИИ ИЗОБРАЖЕНИЙ И РЕАЛИЗАЦИЯ ДВАЖДЫ СТОХАСТИЧЕСКИХ МОДЕЛЕЙ ДЛЯ ПОВЫШЕНИЯ ЭФФЕКТИВНОСТИ …

- ВЕ Дементьев, НА Андриянов

87. 2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge

- Y Gu, Y Pan, S Chen

88. Unsupervised Domain Adaptation from Axial toShort-Axis Multi-Slice Cardiac MR Images byIncorporating Pretrained Task Networks

- S Koehler, T Hussain, Z Blair, T Huffaker

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

- P Shved

90. Single-Shot Cuboids: Geodesics-based End-to-end Manhattan Aligned Layout Estimation from Spherical Panoramas

- N Zioulis, F Alvarez, D Zarpalas, P Daras

91. Analysis of medical images using deep learning

- A Utegulov

92. 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

93. Artificial Intelligence in Quantitative Ultrasound Imaging: A Review

- B Zhou, X Yang, T Liu

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

- J Verecken, D Bol, C De Vleeschouwer

95. 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

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

- Y Bai, H Sezen, A Yilmaz

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

- K Isaienkov, M Yushchuk, V Khramtsov

98. Arrow R-CNN for handwritten diagram recognition

- B Schäfer, M Keuper, H Stuckenschmidt

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

- N Tolstokulakov, E Pavlovskiy

100. Feature-based image registration in structured light endoscopy

- AM Kist, J Zilker, M Döllinger, M Semmler

101. DCNN-based Screw Classification in Automated Disassembly Processes

- E Yildiz, F Wörgötter

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

- N Yavari

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

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

104. Differentiable Data Augmentation with Kornia

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

105. Estimating Displaced Populations from Overhead

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

106. Refinement network for unsupervised on the scene foreground segmentation

- M Pardàs Feliu, G Canet Tarrés

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

- F Maleki, N Muthukrishnan, K Ovens

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

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

109. Learning Accurate Dense Correspondences and When to Trust Them

- P Truong, M Danelljan, L Van Gool

110. 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

111. Multi-Label Contrastive Learning for Abstract Visual Reasoning

- M Małkiński, J Mańdziuk

112. Deep local directional embeddings para detección de objetos

- FE Souto Herrera

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

- AY Kondratiev, H Yaginuma, Y Okada

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

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

115. FlashNeuron: SSD-Enabled Large-Batch Training of Very Deep Neural Networks

- J Bae, J Lee, Y Jin, S Son, S Kim, H Jang

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

- LP Soares, HC Dias, CH Grohmann

117. Application of shared backbone DNNs in ADAS perception systems

- MG Lobanov, DL Sholomov

118. Variational Beam Search for Novelty Detection

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

119. Αναγνώριση προσώπων με τεχνικές βαθιάς μηχανικής μάθησης

- Θ Κασσιώτης

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

- I Saitov, T Polevaya, A Filchenkov

121. Image Stylization for Robust Features

- I Melekhov, GJ Brostow, J Kannala

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

- T Nickchen, S Heindorf

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

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

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

- FVM Perez

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

- C Duan, T Zhang

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

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

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

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

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

- J Mizgajski, A Szymczak, M Morzy

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

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

130. Fiscal classification using convolutional neural network

- N Bindal, R Modi, BK Kaushik

131. CASS Studies

- HEB CASS

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

- LM Ellefsen

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

- FVM Perez

134. Fiche de confidentialité et de diffusion du mémoire

- O Non

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

- A Mehra

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

- НА Андриянов, ДА Андриянов

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

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

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

- AM MORA

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

- Q Liu, M Kampffmeyer, R Jenssen

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

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

141. Underwater Object Detection With Mixed Attention Mechanism And Multi-Enhancement Strategy

- W Chen, B Fan

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

- A Wagh

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

- NF Gusarova, AA Lobantsev, AS Vatian

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

- AY Wagh

145. Synthesize and Segment: Towards Improved Catheter Segmentation via Adversarial Augmentation

- I Ullah, P Chikontwe, H Choi, CH Yoon, SH Park

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

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

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

- J Holmberg

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

- A Zhuchkov, D Prokhorov, V Gusev

149. 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

150. Deep Learning-based Object Understanding for Robotic Manipulation

- JS Moon, HJ Jo, JB Song

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

- VE Dementyiev, NA Andriyanov

152. Encoder-Recurrent Decoder Network for Single Image Dehazing

- A Dang, TH Vu, JC Wang

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

- M Genaev, S Ekaterina

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

- A Kozlov

155. NoGAN: Deblurring Images without Adversarial Training

- R Vei

156. MaskHunter: real-time object detection of face masks during the COVID-19 pandemic

- Z Cao, M Shao, L Xu, S Mu, H Qu

157. SEGMENTATION OF CLOUD PATTERNS FROM SATELLITE IMAGES TO IMPROVE CLIMATE MODELS

- K Vishnyakov, M Organokov

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

- M Scott, J Plested

159. 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

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

- P Miralles Roure

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

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

162. CrackWeb: A modified U-Net based segmentation architecture for crack detection

- S Ghosh, S Singh, A Maity

163. Detecting subsurface drainage pipes using a fully convolutional network with optical images

- H Song, DK Woo, Q Yan

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

- VS Samun, AS Sheka, TV Chumarnaya

165. A Deep learning approach to Hazard detection for Autonomous Lunar landing

- R Moghe, R Zanetti

166. Rubik's Cube layout construction and validation algorithm

- B Borkivskyi

167. Annotation quality vs. quantity for deep-learned medical image segmentation

- T Wesemeyer, ML Jauer

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

- B Liebl, M Burghardt

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

- A Kalinin

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

- CCG Sarasa, JDO Pabón

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

- A Kornilov, I Safonov

172. DAugNet: Unsupervised, Multisource, Multitarget, and Life-Long Domain Adaptation for Semantic Segmentation of Satellite Images

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

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

- D Lacalle, HA Castro-Abril, T Randelovic

174. Variational Beam Search for Online Learning with Distribution Shifts

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

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

- C Sebastian, R Imbriaco, E Bondarev

176. HISTOPATHOLOGY LEARNING DATASET AUGMENTATION: A HYBRID APPROACH

- R HAMDI, C Bouvier, T Delzescaux, C Clouchoux

177. Refinement Network for unsupervised on the scene Foreground Segmentation

- M Pardàs, G Canet

178. Automatic lesion boundary detection in dermoscopy

- G Kechyn

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

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

180. 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

181. Urban Sound Classification: striving towards a fair comparison

- A Arnault, B Hanssens, N Riche

182. ИСПОЛЬЗОВАНИЕ АУГМЕНТАЦИИ ИЗОБРАЖЕНИЙ СОВМЕСТНО С РЕАЛИЗАЦИЕЙ ДВАЖДЫ СТОХАСТИЧЕСКОЙ МОДЕЛИ ДЛЯ УЛУЧШЕНИЯ КАЧЕСТВА …

- НА Андриянов, ВЕ Дементьев

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

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

184. Understanding the decisions of CNNs: An in-model approach

- I Rio-Torto, K Fernandes, LF Teixeira

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

- RB Fricks, J Solomon, E Samei

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

- СВ Кравченко, АВ Алексеев, ЮА Орлова

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

- Y Zharov, A Ershov, T Baumbach

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

- A Moumtzidou, M Bakratsas, S Andreadis

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

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

190. 3DeepM: An Ad Hoc Architecture Based on Deep Learning Methods for Multispectral Image Classification

- PJ Navarro, L Miller, A Gila-Navarro, MV Díaz-Galián

191. Faster R-CNN model learning on synthetic images

- B Łach, E Łukasik

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