Model-based active learning to detect isometric deformable objects in the wild with deep architectures

7 Jun 2018 Shrinivasan Sankar Adrien Bartoli

In the recent past, algorithms based on Convolutional Neural Networks (CNNs) have achieved significant milestones in object recognition. With large examples of each object class, standard datasets train well for inter-class variability... (read more)

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Methods used in the Paper


METHOD TYPE
Max Pooling
Pooling Operations
Batch Normalization
Normalization
Average Pooling
Pooling Operations
1x1 Convolution
Convolutions
Global Average Pooling
Pooling Operations
Darknet-19
Convolutional Neural Networks
YOLOv2
Object Detection Models
Fast R-CNN
Object Detection Models
RPN
Region Proposal
Softmax
Output Functions
Convolution
Convolutions
RoIPool
RoI Feature Extractors
Faster R-CNN
Object Detection Models