Research

Papers for “imagenet”

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

Title	Authors	Year	Source
Towards detection and classification of microscopic foraminifera using transfer learning	Thomas Haugland Johansen, Steffen Aagaard S\orensen	2020	arxiv 2001.04782
Constructing Energy-efficient Mixed-precision Neural Networks through Principal Component Analysis for Edge Intelligence	Indranil Chakraborty, Deboleena Roy, Isha Garg	2019	arxiv 1906.01493
Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training	An Xu, Zhouyuan Huo, Heng Huang	2020	arxiv 2002.11082
XSepConv: Extremely Separated Convolution	Jiarong Chen, Zongqing Lu, Jing-Hao Xue	2020	arxiv 2002.12046
Standard Deviation-Based Quantization for Deep Neural Networks	Amir Ardakani, Arash Ardakani, Brett Meyer	2022	arxiv 2202.12422
Q-TART: Quickly Training for Adversarial Robustness and in-Transferability	Madan Ravi Ganesh, Salimeh Yasaei Sekeh, Jason J. Corso	2022	arxiv 2204.07024
Localizing Semantic Patches for Accelerating Image Classification	Chuanguang Yang, Zhulin An, Yongjun Xu	2022	arxiv 2206.03367
Learning Pruned Structure and Weights Simultaneously from Scratch: an Attention based Approach	Qisheng He, Weisong Shi, Ming Dong	2021	arxiv 2111.02399
Dataset Condensation via Efficient Synthetic-Data Parameterization	Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh	2022	arxiv 2205.14959
General-purpose, long-context autoregressive modeling with Perceiver AR	Curtis Hawthorne, Andrew Jaegle, Cătălina Cangea	2022	arxiv 2202.07765
You Only Cut Once: Boosting Data Augmentation with a Single Cut	Junlin Han, Pengfei Fang, Weihao Li	2022	arxiv 2201.12078
Few-Max: Few-Shot Domain Adaptation for Unsupervised Contrastive Representation Learning	Ali Lotfi Rezaabad, Sidharth Kumar, Sriram Vishwanath	2022	arxiv 2206.10137
Robustness of Epinets against Distributional Shifts	Xiuyuan Lu, Ian Osband, Seyed Mohammad Asghari	2022	arxiv 2207.00137
Efficient Self-supervised Vision Transformers for Representation Learning	Chunyuan Li, Jianwei Yang, Pengchuan Zhang	2021	arxiv 2106.09785
DropNet: Reducing Neural Network Complexity via Iterative Pruning	John Tan Chong Min, Mehul Motani	2022	arxiv 2207.06646
Learning from Multiple Annotator Noisy Labels via Sample-wise Label Fusion	Zhengqi Gao, Fan-Keng Sun, Mingran Yang	2022	arxiv 2207.11327
How Well Do Vision Transformers (VTs) Transfer To The Non-Natural Image Domain? An Empirical Study Involving Art Classification	Vincent Tonkes, Matthia Sabatelli	2022	arxiv 2208.04693
Self-Supervised Pretraining for Differentially Private Learning	Arash Asadian, Evan Weidner, Lei Jiang	2022	arxiv 2206.07125
CYBORGS: Contrastively Bootstrapping Object Representations by Grounding in Segmentation	Renhao Wang, Hang Zhao, Yang Gao	2022	arxiv 2203.09343
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps	Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann	2022	arxiv 2208.11436

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