[PDF] Top 20 Effective and annotation efficient deep learning for image understanding

Effective and annotation efficient deep learning for image understanding

... hand, for the residual based approaches it is easier to learn to predict zero residuals in the case of correct initial labels, but it is more difficult for them to refine “hard” mistakes that deviate a lot ... Voir le document complet

236

Conditional Random Field and Deep Feature Learning for Hyperspectral Image Segmentation

... spectral and spatial information separately in which the spatial information is perceived in advance by the use of spatial filters ...in image segmentation [8], [9]. The second category combines spectral ... Voir le document complet

17

Efficient FPGA-Based Inference Architectures for Deep Learning Networks

... (CNNs) and Deep Neural Networks (DNNs) have gained significant popularity in several classification and regres- sion ...computation and memory requirements of DNN and CNN architectures ... Voir le document complet

117

Deep Learning for Image Memorability Prediction : the Emotional Bias

... knowledge and is highly ...predict image memorability ...frameworks and there is currently no large image datasets with memorability ...an effective paradigm for learning ... Voir le document complet

6

When Deep Learning Meets Digital Image Correlation

... methods for optical flow estimation Optical flow is the apparent displacement field obtained from two views of a ...observer and objects in the scene which may move or ...Horn and Schunck [14] or by ... Voir le document complet

47

Learning an Adaptive Dictionary Structure for Efficient Image Sparse Coding

... dictionary for sparse representations has been explored in [5] with the concept of ITD (Iteration-Tuned ...search and efficient coding of the sparse representations since each dictionary can be kept ... Voir le document complet

5

Efficient deep learning model for mitosis detection using breast histopathology images

... required for breast cancer ...aggressiveness and the proliferation rate of the ...intensive and challenging ...using deep learning architecture with handcrafted ...AMIDA-13 and ... Voir le document complet

28

Natural image processing and synthesis using deep learning

... the image we would like to process, and H O ×W O are the extents of the ...as image processing (e.g., image compression) do not exactly fit the definition ...thesis. Image processing is ... Voir le document complet

175

Review of Recent Deep Learning Based Methods for Image-Text Retrieval

... Representation Learning (ARL) framework to learn modality-invariant representations for more effective image-text ...new deep adversarial graph attention convolution network (A- GANet ... Voir le document complet

7

Curriculum-based transfer learning for an effective end-to-end spoken language understanding and domain portability

... language understanding, neural network, transfer learning, curriculum learning, domain portability ...on deep neural networks for both acoustic and language modelling, perfor- ... Voir le document complet

6

An Efficient Human Activity Recognition Technique Based on Deep Learning

... features and Body modeling tech- ...ture and orientation are ...used for recognition. In [4] Kumari and Mitra proposed a transform-based technique by using dis- crete Fourier transforms (DFTs) ... Voir le document complet

15

Learning Sparse deep neural networks using efficient structured projections on convex constraints for green AI

... memory and computational power. I. M OTIVATION Deep neural networks have been applied recently to different domains and have shown a dramatic improvement in accuracy of image recognition [1], ... Voir le document complet

9

Learning A Tree-Structured Dictionary For Efficient Image Representation With Adaptive Sparse Coding

... curves for the Tree K- SVD method and the state-of-the-art ...representation, for complete (Fig.3), and overcomplete ...is effective when more than 2 atoms are selected in the repre- ... Voir le document complet

6

Deep learning and reinforcement learning methods for grounded goal-oriented dialogue

... with deep learning and reinforcement learning techniques has proven ...domains for which there is not a clear measure of ...objective, and (iii) enables enriching language ... Voir le document complet

164

Deep Learning and Reinforcement Learning for Inventory Control

... enabling and disabling ER is displayed in Figure ...episodes and the final value of cost is lower when the amount of memory of ER ...ER and target Q-network on the results for different case ... Voir le document complet

69

Deep learning methods for the design and understanding of solid materials

... where for RS the BSF value plateaus after around 50 random ...efficiently, and converges to a much higher conductivity within only around 60 iterations, ...an efficient approach for SPE ... Voir le document complet

145

Deep Bilateral Learning for Real-Time Image Enhancement

... used for such learning are also far from ...[2016], and a linear network based on dilated convolutions [Yu and Koltun ...settings for the depth (number of layers, 3 to 11) and ... Voir le document complet

13

Random Subwindows and Randomized Trees for Image Retrieval, Classification, and Annotation

... state-of-the-art and to manual ...tool for further biological ...method and first try in various biological studies that can be formulated as image retrieval, classification or segmentation ... Voir le document complet

1

Deep learning for cloud detection

... the image. 6 Conclusion Deep learning offers the possibility to build really complex and robust ...computing and Graphical Processing Units, convolutional networks are faster to ... Voir le document complet

7

Deep Learning for Video Modelling

... hope for sequences RNN-like approaches to this ...alternative for UCF101, with ...capacity for detection in time since everything not moving will create edges in this ...input for their ... Voir le document complet

90