Research

Papers for “imagenet”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

Title	Authors	Year	Source
Phased Progressive Learning with Coupling-Regulation-Imbalance Loss for Imbalanced Data Classification	Liang Xu, Yi Cheng, Fan Zhang	2022	arxiv 2205.12117
Sampling-based inference for large linear models, with application to linearised Laplace	Javier Antorán, Shreyas Padhy, Riccardo Barbano	2022	arxiv 2210.04994
Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations	Lei Hsiung, Yun-Yun Tsai, Pin-Yu Chen	2022	arxiv 2202.04235
Parameter-Free Channel Attention for Image Classification and Super-Resolution	Yuxuan Shi, Lingxiao Yang, Wangpeng An	2023	arxiv 2303.11055
NoisyTwins: Class-Consistent and Diverse Image Generation through StyleGANs	Harsh Rangwani, Lavish Bansal, Kartik Sharma	2023	arxiv 2304.05866
Zero-shot Unsupervised Transfer Instance Segmentation	Gyungin Shin, Samuel Albanie, Weidi Xie	2023	arxiv 2304.14376
A Study on Transformer Configuration and Training Objective	Fuzhao Xue, Jianghai Chen, Aixin Sun	2022	arxiv 2205.10505
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models	Dongjun Kim, Yeongmin Kim, Se Jung Kwon	2022	arxiv 2211.17091
3D Object Classification via Spherical Projections	Zhangjie Cao, Qixing Huang, Karthik Ramani	2017	arxiv 1712.04426
CNNs are Globally Optimal Given Multi-Layer Support	Chen Huang, Chen Kong, Simon Lucey	2017	arxiv 1712.02501
Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images	Hongliu Cao, Simon Bernard, Laurent Heutte	2018	arxiv 1803.11241
Progressive Neural Networks for Image Classification	Zhi Zhang, Guanghan Ning, Yigang Cen	2018	arxiv 1804.09803
IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks	Ke Sun, Mingjie Li, Dong Liu	2018	arxiv 1806.00178
Diagnosing Convolutional Neural Networks using their Spectral Response	Victor Stamatescu, Mark D. McDonnell	2018	arxiv 1810.03241
Collaborative Learning for Deep Neural Networks	Guocong Song, Wei Chai	2018	arxiv 1805.11761
Do Normalization Layers in a Deep ConvNet Really Need to Be Distinct?	Ping Luo, Zhanglin Peng, Jiamin Ren	2018	arxiv 1811.07727
Deep Q learning for fooling neural networks	Mandar Kulkarni	2018	arxiv 1811.05521
A Convolutional Neural Network based Live Object Recognition System as Blind Aid	Kedar Potdar, Chinmay D. Pai, Sukrut Akolkar	2018	arxiv 1811.10399
Deep Defense: Training DNNs with Improved Adversarial Robustness	Ziang Yan, Yiwen Guo, Changshui Zhang	2018	arxiv 1803.00404
Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation	Jiaxin Gu, Ce Li, Baochang Zhang	2018	arxiv 1811.12755

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