Inverse Feature Learning: Feature Learning Based on Representation Learning of Error by Behzad Ghazanfari, Fatemeh Afghah, Mohammadtaghi Hajiaghayi

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Compact feature learning for multimedia retrieval by Liong, Venice Erin Baylon

“…Particularly, we present four compact feature learning methods. Experimental results in benchmark retrieval datasets and comparisons with popular feature learning and hashing methods have demonstrated the effectiveness of our proposed methods.…”
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Hierarchical feature learning for image categorization by Zuo, Zhen

“…The goal of this thesis is to present various feature learning architectures for the problem of object/scene image categorization. …”
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Human face segmentation and feature learning by Winarta, Ferdian

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On kernel and feature learning in neural networks by He, B

“…<p>Inspired by the theory of wide neural networks (NNs), kernel learning and feature learning have recently emerged as two paradigms through which we can understand the complex behaviours of large-scale deep learning systems in practice. …”

Omnidirectional Feature Learning for Person Re-Identification by Di Wu, Hong-Wei Yang, De-Shuang Huang, Chang-An Yuan, Xiao Qin, Yang Zhao, Xin-Yong Zhao, Jian-Hong Sun

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Discriminating features learning in hand gesture classification by Feng Jiang, Cuihua Wang, Yang Gao, Shen Wu, Debin Zhao

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Feature Learning and Analysis for Cleanliness Classification in Restrooms by Lahiru Jayasinghe, Nipun Wijerathne, Chau Yuen, Meng Zhang

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Feature learning for RGB-D scene understanding by Wang, Anran

“…Inspired by the success of unsupervised feature learning, we start by adapting the existing unsupervised feature learning technique to directly learn features from RGB-D images. …”
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DNet: Dynamic Neighborhood Feature Learning in Point Cloud by Fujing Tian, Zhidi Jiang, Gangyi Jiang

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Multi-Scale Adversarial Feature Learning for Saliency Detection by Dandan Zhu, Lei Dai, Ye Luo, Guokai Zhang, Xuan Shao, Laurent Itti, Jianwei Lu

“…Since the GAN shows a superior feature learning ability, we present a new multi-scale adversarial feature learning (MAFL) model for image saliency detection. …”
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Unsupervised feature learning-based encoder and adversarial networks by Endang Suryawati, Hilman F. Pardede, Vicky Zilvan, Ade Ramdan, Dikdik Krisnandi, Ana Heryana, R. Sandra Yuwana, R. Budiarianto Suryo Kusumo, Andria Arisal, Ahmad Afif Supianto

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Age-Invariant Adversarial Feature Learning for Kinship Verification by Fan Liu, Zewen Li, Wenjie Yang, Feng Xu

“…This paper accordingly proposes an Age-Invariant Adversarial Feature learning module (AIAF), which is capable of factoring in full facial features to create two uncorrelated components, i.e., identity-related features and age-related features. …”
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Feature Learning Viewpoint of Adaboost and a New Algorithm by Fei Wang, Zhongheng Li, Fang He, Rong Wang, Weizhong Yu, Feiping Nie

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Pairwise Constraints Multidimensional Scaling for Discriminative Feature Learning by Linghao Zhang, Bo Pang, Haitao Tang, Hongjun Wang, Chongshou Li, Zhipeng Luo

Subjects: “…discriminative feature learning…”
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Disentangled Feature Learning for Noise-Invariant Speech Enhancement by Soo Hyun Bae, Inkyu Choi, Nam Soo Kim

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Structure-enhanced pairwise feature learning for face clustering by Shaoying Li, Jie Li, Bincheng Wang, Wei Yao, Bo Liu

“…Specifically, we propose a novel clustering framework, named structure-enhanced pairwise feature learning (SEPFL), which mixes neighborhood information to adaptively produce pairwise representations for cluster identification. …”
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Feature Learning Based Random Walk for Liver Segmentation. by Yongchang Zheng, Danni Ai, Pan Zhang, Yefei Gao, Likun Xia, Shunda Du, Xinting Sang, Jian Yang

“…This paper proposes a feature-learning-based random walk method for liver segmentation using CT images. …”
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Broad Learning Model Based on Enhanced Features Learning by Qingmei Zhou, Xiping He

“…This shows that the broad learning model based on enhanced features learning has the necessity and feasibility of further research.…”
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Robust Vehicle Classification Based on Deep Features Learning by Naghmeh Niroomand, Christian Bach, Miriam Elser

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