| You Only Look Once: Unified, Real-Time Object Detection
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| SSD: Single Shot MultiBox Detector
| [0042]
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| Faster R-CNN: Toward Real-Time Object Detection with Region Proposal Networks
| [0042]
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| MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
| [0042]
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| Simple Online and Realtime Tracking with a Deep Association Metric
| [0043]
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| Tracking without bells and whistles
| [0043]
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| Deep Learning in Video Multi-Object Tracking: A Survey
| [0043]
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| Extending IOU Based Multi-Object Tracking by Visual Information
| [0043]
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| Tracking Objects as Points
| [0043]
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| Online Multiple Pedestrians Tracking using Deep Temporal Appearance Matching Association
| [0043]
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| Object Tracking using OpenCV (C++ / Python)
| [0043]
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| Deep Residual Learning for Image Recognition
| [0046]
[0081]
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| Rethinking the Inception Architecture for Computer Vision
| [0046]
[0081]
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| EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
| [0046]
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| EfficientNet-eLite: Extremely Lightweight and Efficient CNN Models for Edge Devices by Network Candidate Search
| [0046]
[0081]
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| End-to-end deep learning-based autonomous driving control for high-speed environment
| [0047]
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| Toward End-to-End Control for UAV Autonomous Landing via Deep Reinforcement Learning
| [0047]
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| Deep Learning based Feature Extraction for Texture Classification
| [0048]
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| Spatial-Temporal Recurrent Neural Network for Emotion Recognition
| [0063]
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| A Hybrid Spatial-temporal Deep Learning Architecture for Lane Detection
| [0063]
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| VoxelMorph: A Learning Framework for Deformable Medical Image Registration
| [0066]
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| Convolutional neural network architecture for geometric matching
| [0066]
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| Spatial Transformer Networks
| [0067]
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| Attentive Semantic Alignment with Offset-Aware Correlation Kernels
| [0067]
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| Video Foreground Detection Algorithm Based on Fast Principal Component Pursuit and Motion Saliency
| [0068]
[0106]
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| Robust Principal Component Analysis?
| [0068]
[0106]
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| Good features to track
| [0071]
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| Machine learning for high-speed corner detection
| [0071]
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| Adaptive and generic corner detection based on the accelerated segment test
| [0071]
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| Scale & Affine Invariant Interest Point Detectors
| [0071]
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| CenSurE: Center surround extremas for real time feature detection and matching
| [0071]
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| Distinctive Image Features from Scale-Invariant Keypoints
| [0071]
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| ORB: An efficient alternative to SIFT or SURF
| [0071]
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| BRISK: Binary Robust invariant scalable keypoints
| [0071]
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| Fast explicit diffusion for accelerated features in nonlinear scale spaces
| [0072]
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| Kaze features
| [0072]
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| Freak: Fast retina keypoint
| [0072]
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| Brief: Computing a local binary descriptor very fast
| [0072]
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| Daisy: An Efficient Dense Descriptor Applied to Wide Baseline Stereo
| [0072]
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| Latch: Learned arrangements of three patch codes
| [0072]
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| Very deep convolutional networks for large-scale image recognition
| [0072]
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| EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,สบ
| [0081]
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| Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
| [0082]
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| Uncertainty Quantification and Deep Ensembles
| [0082]
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| Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
| [0083]
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| Layer-Wise Relevance Propagation: An Overview
| [0083]
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| Axiomatic Attribution for Deep Networks
| [0083]
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| Learning How to Explain Neural Networks: PatternNet and PatternAttribution
| [0083]
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| The adoption of deep learning interpretability techniques on diabetic retinopathy analysis: a review
| [0083]
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| Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
| [0083]
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| Visualizing and Understanding Convolutional Networks
| [0083]
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| Robust Template Matching via Hierarchical Convolutional Features from a Shape Biased CNN
| [0084]
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