Journals starting with dee

DeepAffective17 * *Deep Affective Learning and Context Modeling
* Action-Affect-Gender Classification Using Multi-task Representation Learning
* DeepSpace: Mood-Based Image Texture Generation for Virtual Reality from Music
* DyadGAN: Generating Facial Expressions in Dyadic Interactions
* EMOTIC: Emotions in Context Dataset
* Exploring Contextual Engagement for Trauma Recovery
* Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networks
* It's Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation
* Personalized Automatic Estimation of Self-Reported Pain Intensity from Facial Expressions
* Speech-Driven 3D Facial Animation with Implicit Emotional Awareness: A Deep Learning Approach
10 for DeepAffective17

DeepLearn-C16 * *Deep Vision: Deep Learning in Computer Vision
* Adversarial Diversity and Hard Positive Generation
* Deep End2End Voxel2Voxel Prediction
* Faster R-CNN Features for Instance Search
* Joint Learning of Convolutional Neural Networks and Temporally Constrained Metrics for Tracklet Association
* Learning by Tracking: Siamese CNN for Robust Target Association
* ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation
* Rich Image Captioning in the Wild
8 for DeepLearn-C16

DeepLearn-T17 * *Deep Vision: Deep Learning in Computer Vision
* Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition
* Crowd-11: A Dataset for Fine Grained Crowd Behaviour Analysis
* Fixation Prediction in Videos Using Unsupervised Hierarchical Features
* Kernalised Multi-resolution Convnet for Visual Tracking
* Learning Latent Temporal Connectionism of Deep Residual Visual Abstractions for Identifying Surgical Tools in Laparoscopy Procedures
* Recurrent Memory Addressing for Describing Videos
* SANet: Structure-Aware Network for Visual Tracking
* Temporal Domain Neural Encoder for Video Representation Learning
* Temporally Steered Gaussian Attention for Video Understanding
10 for DeepLearn-T17

DeepLearn14 * *Deep Vision: Deep Learning in Computer Vision
* CNN Features Off-the-Shelf: An Astounding Baseline for Recognition
* Generalized Autoencoder: A Neural Network Framework for Dimensionality Reduction
* Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network
* Piggyback Representation for Action Recognition, A
* Unrolling Loopy Top-Down Semantic Feedback in Convolutional Deep Networks

DeepLearn15 * *Deep Vision: Deep Learning in Computer Vision
* Channel-Max, Channel-Drop and Stochastic Max-pooling
* Color constancy using CNNs
* Convolutional recurrent neural networks: Learning spatial dependencies for image representation
* Deep learning of binary hash codes for fast image retrieval
* Exploiting local features from deep networks for image retrieval
* From generic to specific deep representations for visual recognition
* Learning to count with deep object features
* Multi-scale pyramid pooling for deep convolutional representation
* Object level deep feature pooling for compact image representation
* Self-tuned deep super resolution
* Subset feature learning for fine-grained category classification
12 for DeepLearn15

DeepLearn16 * *Deep Vision: Deep Learning in Computer Vision
* 3D Human Pose Estimation Using Convolutional Neural Networks with 2D Pose Information
* Class-Specific Object Pose Estimation and Reconstruction Using 3D Part Geometry
* CNN Cascade for Landmark Guided Semantic Part Segmentation, A
* Deep Disentangled Representations for Volumetric Reconstruction
* Deep Kinematic Pose Regression
* Deep Shape from a Low Number of Silhouettes
* gvnn: Neural Network Library for Geometric Computer Vision
* How Useful Is Photo-Realistic Rendering for Visual Learning?
* Improving Constrained Bundle Adjustment Through Semantic Scene Labeling
* Learning Covariant Feature Detectors
* Learning the Structure of Objects from Web Supervision
* Monocular Surface Reconstruction Using 3D Deformable Part Models
* On-Line Large Scale Semantic Fusion
* Overcoming Occlusion with Inverse Graphics
* Scene Segmentation Driven by Deep Learning and Surface Fitting
* VConv-DAE: Deep Volumetric Shape Learning Without Object Labels
17 for DeepLearn16

DeepLearnRV17 * *Deep Learning for Robotic Vision
* 3D Pose Regression Using Convolutional Neural Networks
* Automated Risk Assessment for Scene Understanding and Domestic Robots Using RGB-D Data and 2.5D CNNs at a Patch Level
* Curiosity-Driven Exploration by Self-Supervised Prediction
* Detecting and Grouping Identical Objects for Region Proposal and Classification
* End-to-End Driving in a Realistic Racing Game with Deep Reinforcement Learning
* Episode-Based Active Learning with Bayesian Neural Networks
* Finding Anomalies with Generative Adversarial Networks for a Patrolbot
* Hand Movement Prediction Based Collision-Free Human-Robot Interaction
* Learning Robot Activities from First-Person Human Videos Using Convolutional Future Regression
* Leveraging Deep Reinforcement Learning for Reaching Robotic Tasks
* Real-Time Hand Grasp Recognition Using Weakly Supervised Two-Stage Convolutional Neural Networks for Understanding Manipulation Actions
* Semantic Instance Segmentation for Autonomous Driving
* Time-Contrastive Networks: Self-Supervised Learning from Multi-view Observation
* Tuning Modular Networks with Weighted Losses for Hand-Eye Coordination
15 for DeepLearnRV17

DeepLearnV14 * *Deep Learning on Visual Data
* Deep Learning in the EEG Diagnosis of Alzheimer's Disease
* Human Action Recognition Using Action Bank Features and Convolutional Neural Networks
* Hybrid CNN-HMM Model for Street View House Number Recognition
* Pedestrian Detection with Deep Convolutional Neural Network
* View and Illumination Invariant Object Classification Based on 3D Color Histogram Using Convolutional Neural Networks

DeepVisual16 * *Interpretation and Visualization of Deep Neural Nets
* Dense Residual Pyramid Networks for Salient Object Detection
* Fine-Tuning Deep Neural Networks in Continuous Learning Scenarios
* Glance and Glimpse Network: A Stochastic Attention Model Driven by Class Saliency
* Image Patch Matching Using Convolutional Descriptors with Euclidean Distance
* Multi-Scale Hierarchy Deep Feature Aggregation for Compact Image Representations
* Quantitative Analysis of a Bioplausible Model of Misperception of Slope in the Café Wall Illusion
7 for DeepVisual16

Index for "d"

Last update:22-Sep-17 22:09:23
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