Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Object Detection with Deep Learning: A Review   Due to object detection's close relationship with video analysis and image
understanding, it has attracted much research attention in recent years.
Traditional object detection methods are built on handcrafted features and
shallow trainable architectures. Their performance easily stagnates by
constructing complex ensembles which combine multiple low-level image features
with high-level context from object detectors and scene classifiers. With the
rapid development in deep learning, more powerful tools, which are able to
learn semantic, high-level, deeper features, are introduced to address the
problems existing in traditional architectures. These models behave differently
in network architecture, training strategy and optimization function, etc. In
this paper, we provide a review on deep learning based object detection
frameworks. Our review begins with a brief introduction on the history of deep
learning and its representative tool, namely Convolutional Neural Network
(CNN). Then we focus on typical generic object detection architectures along
with some modifications and useful tricks to improve detection performance
further. As distinct specific detection tasks exhibit different
characteristics, we also briefly survey several specific tasks, including
salient object detection, face detection and pedestrian detection. Experimental
analyses are also provided to compare various methods and draw some meaningful
conclusions. Finally, several promising directions and tasks are provided to
serve as guidelines for future work in both object detection and relevant
neural network based learning systems.

10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
20
The categories of this paper are: acc-phys
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
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The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
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The categories of this paper are: math-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: q-alg
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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg