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04/05/2021
Branch-and-Pruning Optimization Towards Global Optimality in Deep Learning
It has been attracting more and more attention to understand the global ...
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01/05/2020
Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters
In this paper, we investigate the empirical impact of orthogonality regu...
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12/10/2019
MDFN: Multi-Scale Deep Feature Learning Network for Object Detection
This paper proposes an innovative object detector by leveraging deep fea...
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12/04/2019
Object Detection with Convolutional Neural Networks
In this chapter, we present a brief overview of the recent development i...
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10/04/2019
Adaptively Denoising Proposal Collection for Weakly Supervised Object Localization
In this paper, we address the problem of weakly supervised object locali...
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08/27/2019
Unsupervised Deep Feature Transfer for Low Resolution Image Classification
In this paper, we propose a simple while effective unsupervised deep fea...
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09/06/2018
MDCN: Multi-Scale, Deep Inception Convolutional Neural Networks for Efficient Object Detection
Object detection in challenging situations such as scale variation, occl...
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11/19/2017
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning
Understanding the global optimality in deep learning (DL) has been attra...
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03/19/2017
