Search Results for author: Jian Chen

Found 68 papers, 25 papers with code

DeepPaperComposer: A Simple Solution for Training Data Preparation for Parsing Research Papers

no code implementations EMNLP (sdp) 2020 Meng Ling, Jian Chen

We present DeepPaperComposer, a simple solution for preparing highly accurate (100%) training data without manual labeling to extract content from scholarly articles using convolutional neural networks (CNNs).

FinTextQA: A Dataset for Long-form Financial Question Answering

no code implementations16 May 2024 Jian Chen, Peilin Zhou, Yining Hua, Yingxin Loh, Kehui Chen, Ziyuan Li, Bing Zhu, Junwei Liang

Accurate evaluation of financial question answering (QA) systems necessitates a comprehensive dataset encompassing diverse question types and contexts.

Long Form Question Answering Retrieval

Efficient Pretraining Model based on Multi-Scale Local Visual Field Feature Reconstruction for PCB CT Image Element Segmentation

no code implementations9 May 2024 Chen Chen, Kai Qiao, Jie Yang, Jian Chen, Bin Yan

In this model, the teacher-guided MIM pretraining model is introduced into PCB CT image element segmentation for the first time, and a multi-scale local visual field extraction (MVE) module is proposed to reduce redundancy by focusing on local visual fields.

Computed Tomography (CT) Segmentation

Outlier Gradient Analysis: Efficiently Improving Deep Learning Model Performance via Hessian-Free Influence Functions

no code implementations6 May 2024 Anshuman Chhabra, Bo Li, Jian Chen, Prasant Mohapatra, Hongfu Liu

Influence functions offer a robust framework for assessing the impact of each training data sample on model predictions, serving as a prominent tool in data-centric learning.

Segmented Model-Based Hydrogen Delivery Control for PEM Fuel Cells: a Port-Hamiltonian Approach

no code implementations18 Apr 2024 Lalitesh Kumar, Jian Chen, Chengshuai Wu, Yuzhu Chen, Arjan van der Schaft

With consideration of re-circulation and bleeding of the anode in the modeling, an extended energy-shaping and output tracking IDA-PBC based state-feedback controller is proposed to control the spatially distributed pressure dynamics in the anode.

Exploring the Necessity of Visual Modality in Multimodal Machine Translation using Authentic Datasets

no code implementations9 Apr 2024 Zi Long, Zhenhao Tang, Xianghua Fu, Jian Chen, Shilong Hou, Jinze Lyu

Recent research in the field of multimodal machine translation (MMT) has indicated that the visual modality is either dispensable or offers only marginal advantages.

Multimodal Machine Translation Sentence +1

An Image-based Typology for Visualization

no code implementations7 Mar 2024 Jian Chen, Petra Isenberg, Robert S. Laramee, Tobias Isenberg, Michael Sedlmair, Torsten Moeller, Rui Li

In addition to the visualization typology from images, we provide a dataset of 6, 833 tagged images and an online tool that can be used to explore and analyze the large set of labeled images.

Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints

1 code implementation7 Feb 2024 Jian Chen, Ruiyi Zhang, Yufan Zhou, Rajiv Jain, Zhiqiang Xu, Ryan Rossi, Changyou Chen

Controllable layout generation refers to the process of creating a plausible visual arrangement of elements within a graphic design (e. g., document and web designs) with constraints representing design intentions.

Layout Design

Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous Driving

1 code implementation11 Oct 2023 Xinyu Zhang, Li Wang, Jian Chen, Cheng Fang, Lei Yang, Ziying Song, Guangqi Yang, Yichen Wang, Xiaofei Zhang, Jun Li, Zhiwei Li, Qingshan Yang, Zhenlin Zhang, Shuzhi Sam Ge

Compared with commonly used 3D radars, the latest 4D radars have precise vertical resolution and higher point cloud density, making it a highly promising sensor for autonomous driving in complex environmental perception.

3D Object Detection Autonomous Driving +1

Can AI Mitigate Human Perceptual Biases? A Pilot Study

no code implementations10 Oct 2023 Ross Geuy, Nate Rising, Tiancheng Shi, Meng Ling, Jian Chen

Our pilot study showed that participants were faster with AI assistance in ensemble tasks, compared to the baseline without AI assistance.

Demonstration-based learning for few-shot biomedical named entity recognition under machine reading comprehension

no code implementations12 Aug 2023 Leilei Su, Jian Chen, Yifan Peng, Cong Sun

The objective of this study is to devise a strategy that can improve the model's capability to recognize biomedical entities in scenarios of few-shot learning.

Few-Shot Learning Machine Reading Comprehension +2

Learning under Selective Labels with Data from Heterogeneous Decision-makers: An Instrumental Variable Approach

no code implementations13 Jun 2023 Jian Chen, Zhehao Li, Xiaojie Mao

The labeled data distribution may substantially differ from the full population, especially when the historical decisions and the target outcome can be simultaneously affected by some unobserved factors.

Decision Making Selection bias

Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels

1 code implementation NeurIPS 2023 Jian Chen, Ruiyi Zhang, Tong Yu, Rohan Sharma, Zhiqiang Xu, Tong Sun, Changyou Chen

Remarkably, by incorporating conditional information from the powerful CLIP model, our method can boost the current SOTA accuracy by 10-20 absolute points in many cases.

 Ranked #1 on Image Classification on Food-101N (using extra training data)

Image Classification Retrieval

NPS: A Framework for Accurate Program Sampling Using Graph Neural Network

no code implementations18 Apr 2023 Yuanwei Fang, Zihao Liu, Yanheng Lu, Jiawei Liu, Jiajie Li, Yi Jin, Jian Chen, Yenkuang Chen, Hongzhong Zheng, Yuan Xie

Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings.

RF-GNN: Random Forest Boosted Graph Neural Network for Social Bot Detection

1 code implementation14 Apr 2023 Shuhao Shi, Kai Qiao, Jie Yang, Baojie Song, Jian Chen, Bin Yan

This paper proposes a Random Forest boosted Graph Neural Network for social bot detection, called RF-GNN, which employs graph neural networks (GNNs) as the base classifiers to construct a random forest, effectively combining the advantages of ensemble learning and GNNs to improve the accuracy and robustness of the model.

Ensemble Learning feature selection +1

Over-Sampling Strategy in Feature Space for Graphs based Class-imbalanced Bot Detection

1 code implementation14 Feb 2023 Shuhao Shi, Kai Qiao, Jie Yang, Baojie Song, Jian Chen, Bin Yan

The proposed framework is evaluated using three real-world bot detection benchmark datasets, and it consistently exhibits superiority over the baselines.

MGTAB: A Multi-Relational Graph-Based Twitter Account Detection Benchmark

1 code implementation3 Jan 2023 Shuhao Shi, Kai Qiao, Jian Chen, Shuai Yang, Jie Yang, Baojie Song, Linyuan Wang, Bin Yan

However, in addition to low annotation quality, existing benchmarks generally have incomplete user relationships, suppressing graph-based account detection research.

Node Classification Stance Detection +1

Boosting Semi-Supervised Learning with Contrastive Complementary Labeling

no code implementations13 Dec 2022 Qinyi Deng, Yong Guo, Zhibang Yang, Haolin Pan, Jian Chen

In this way, these data can be also very informative if we can effectively exploit these complementary labels, i. e., the classes that a sample does not belong to.

Contrastive Learning

Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images

no code implementations ICCV 2023 Bingna Xu, Yong Guo, Luoqian Jiang, Mianjie Yu, Jian Chen

Inspired by this, we propose a Hierarchical Collaborative Downscaling (HCD) method that performs gradient descent in both HR and LR domains to improve the downscaled representations.

Image Reconstruction Super-Resolution

Text-Aware Dual Routing Network for Visual Question Answering

no code implementations17 Nov 2022 Luoqian Jiang, Yifan He, Jian Chen

To address the above issues, we propose a Text-Aware Dual Routing Network (TDR) which simultaneously handles the VQA cases with and without understanding text information in the input images.

Optical Character Recognition Optical Character Recognition (OCR) +2

Pareto-aware Neural Architecture Generation for Diverse Computational Budgets

1 code implementation14 Oct 2022 Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan

More critically, these independent search processes cannot share their learned knowledge (i. e., the distribution of good architectures) with each other and thus often result in limited search results.

Improving Fine-tuning of Self-supervised Models with Contrastive Initialization

1 code implementation30 Jul 2022 Haolin Pan, Yong Guo, Qinyi Deng, Haomin Yang, Yiqun Chen, Jian Chen

Self-supervised learning (SSL) has achieved remarkable performance in pretraining the models that can be further used in downstream tasks via fine-tuning.

Self-Supervised Learning

Towards Lightweight Super-Resolution with Dual Regression Learning

2 code implementations16 Jul 2022 Yong Guo, Jingdong Wang, Qi Chen, JieZhang Cao, Zeshuai Deng, Yanwu Xu, Jian Chen, Mingkui Tan

Nevertheless, it is hard for existing model compression methods to accurately identify the redundant components due to the extremely large SR mapping space.

Image Super-Resolution Model Compression +1

Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks

no code implementations8 May 2022 Shuhao Shi, Jian Chen, Kai Qiao, Shuai Yang, Linyuan Wang, Bin Yan

The Graph Convolutional Networks (GCNs) have achieved excellent results in node classification tasks, but the model's performance at low label rates is still unsatisfactory.

Node Classification

Forex Trading Volatility Prediction using Neural Network Models

no code implementations2 Dec 2021 Shujian Liao, Jian Chen, Hao Ni

In this paper, we investigate the problem of predicting the future volatility of Forex currency pairs using the deep learning techniques.

Attribute-specific Control Units in StyleGAN for Fine-grained Image Manipulation

1 code implementation25 Nov 2021 Rui Wang, Jian Chen, Gang Yu, Li Sun, Changqian Yu, Changxin Gao, Nong Sang

Image manipulation with StyleGAN has been an increasing concern in recent years. Recent works have achieved tremendous success in analyzing several semantic latent spaces to edit the attributes of the generated images. However, due to the limited semantic and spatial manipulation precision in these latent spaces, the existing endeavors are defeated in fine-grained StyleGAN image manipulation, i. e., local attribute translation. To address this issue, we discover attribute-specific control units, which consist of multiple channels of feature maps and modulation styles.

Attribute Image Manipulation

A novel multiobjective evolutionary algorithm based on decomposition and multi-reference points strategy

no code implementations27 Oct 2021 Wang Chen, Jian Chen, Weitian Wu, Xinmin Yang, Hui Li

For performance assessment, the proposed algorithm is compared with existing four state-of-the-art multiobjective evolutionary algorithms on benchmark test problems with various types of Pareto optimal fronts.

Evolutionary Algorithms Multiobjective Optimization

Efficient Second-Order Optimization for Deep Learning with Kernel Machines

no code implementations29 Sep 2021 Yawen Chen, Zeyi Wen, Yile Chen, Jian Chen, Jin Huang

However, the recomputation of the Hessian matrix in the second-order optimization posts much extra computation and memory burden in the training.

Adaptive Multi-layer Contrastive Graph Neural Networks

no code implementations29 Sep 2021 Shuhao Shi, Pengfei Xie, Xu Luo, Kai Qiao, Linyuan Wang, Jian Chen, Bin Yan

AMC-GNN generates two graph views by data augmentation and compares different layers' output embeddings of Graph Neural Network encoders to obtain feature representations, which could be used for downstream tasks.

Data Augmentation Self-Supervised Learning

Indoor Localization Using Smartphone Magnetic with Multi-Scale TCN and LSTM

no code implementations24 Sep 2021 Mingyang Zhang, Jie Jia, Jian Chen

A novel multi-scale temporal convolutional network (TCN) and long short-term memory network (LSTM) based magnetic localization approach is proposed.

Indoor Localization Time Series +1

Content-Aware Convolutional Neural Networks

1 code implementation30 Jun 2021 Yong Guo, Yaofo Chen, Mingkui Tan, Kui Jia, Jian Chen, Jingdong Wang

In practice, the convolutional operation on some of the windows (e. g., smooth windows that contain very similar pixels) can be very redundant and may introduce noises into the computation.

Caching and Computation Offloading in High Altitude Platform Station (HAPS) Assisted Intelligent Transportation Systems

no code implementations28 Jun 2021 Qiqi Ren, Omid Abbasi, Gunes Karabulut Kurt, Halim Yanikomeroglu, Jian Chen

In addition, the caching technique is introduced for network edges to store some of the fundamental data from the HAPS so that large propagation delays can be reduced.


Document Domain Randomization for Deep Learning Document Layout Extraction

no code implementations20 May 2021 Meng Ling, Jian Chen, Torsten Möller, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Robert S. Laramee, Han-Wei Shen, Jian Wu, C. Lee Giles

We present document domain randomization (DDR), the first successful transfer of convolutional neural networks (CNNs) trained only on graphically rendered pseudo-paper pages to real-world document segmentation.

Document Layout Analysis

De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks

no code implementations8 May 2021 Jian Chen, Xuxin Zhang, Rui Zhang, Chen Wang, Ling Liu

The results demonstrate that De-Pois is effective and efficient for detecting poisoned data against all the four types of poisoning attacks, with both the accuracy and F1-score over 0. 9 on average.

Data Augmentation Data Poisoning

Learning Defense Transformers for Counterattacking Adversarial Examples

1 code implementation13 Mar 2021 Jincheng Li, JieZhang Cao, Yifan Zhang, Jian Chen, Mingkui Tan

Relying on this, we learn a defense transformer to counterattack the adversarial examples by parameterizing the affine transformations and exploiting the boundary information of DNNs.

Adversarial Defense

Digital Interference Mitigation in Space Division Multiplexing Self-Homodyne Coherent Detection

no code implementations28 Feb 2021 Hanzi Huang, Yetian Huang, Haoshuo Chen, Qianwu Zhang, Jian Chen, Nicolas K. Fontaine, Mikael Mazur, Roland Ryf, Junho Cho, Yingxiong Song

We propose a digital interference mitigation scheme to reduce the impact of mode coupling in space division multiplexing self-homodyne coherent detection and experimentally verify its effectiveness in 240-Gbps mode-multiplexed transmission over 3-mode multimode fiber.

Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets

no code implementations27 Feb 2021 Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan

To this end, we propose a Pareto-Frontier-aware Neural Architecture Generator (NAG) which takes an arbitrary budget as input and produces the Pareto optimal architecture for the target budget.

Calibration of manganin pressure gauge for diamond-anvil cells

no code implementations24 Feb 2021 Jian Chen, Hu Cheng, Xuefeng Zhou, Xiaozhi Yan, Lingfei Wang, Yusheng Zhao, Shanmin Wang

However, the ruby scale can often hardly be used for programmably-controlled DAC devices, especially the piezoelectric-driving cells, where a continuous pressure calibration is required.

Applied Physics Materials Science

Towards Accurate and Compact Architectures via Neural Architecture Transformer

2 code implementations20 Feb 2021 Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao, Junzhou Huang

To address this issue, we propose a Neural Architecture Transformer++ (NAT++) method which further enlarges the set of candidate transitions to improve the performance of architecture optimization.

Neural Architecture Search valid

Pareto-Frontier-aware Neural Architecture Search

no code implementations1 Jan 2021 Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan

To find promising architectures under different budgets, existing methods may have to perform an independent search for each budget, which is very inefficient and unnecessary.

Neural Architecture Search

VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications

no code implementations22 Dec 2020 Jian Chen, Meng Ling, Rui Li, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Torsten Möller, Robert S. Laramee, Han-Wei Shen, Katharina Wünsche, Qiru Wang

We present the VIS30K dataset, a collection of 29, 689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST).

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking

1 code implementation14 Dec 2020 Jiachun Wang, Fajie Yuan, Jian Chen, Qingyao Wu, Min Yang, Yang Sun, Guoxiao Zhang

We validate the performance of StackRec by instantiating it with four state-of-the-art SR models in three practical scenarios with real-world datasets.

Sequential Recommendation

Defense-guided Transferable Adversarial Attacks

no code implementations22 Oct 2020 Zifei Zhang, Kai Qiao, Jian Chen, Ningning Liang

Experimentally, we show that our ASR of adversarial attack reaches to 58. 38% on average, which outperforms the state-of-the-art method by 12. 1% on the normally trained models and by 11. 13% on the adversarially trained models.

Adversarial Attack

Double Forward Propagation for Memorized Batch Normalization

no code implementations10 Oct 2020 Yong Guo, Qingyao Wu, Chaorui Deng, Jian Chen, Mingkui Tan

Although the standard BN can significantly accelerate the training of DNNs and improve the generalization performance, it has several underlying limitations which may hamper the performance in both training and inference.

Grasp Proposal Networks: An End-to-End Solution for Visual Learning of Robotic Grasps

2 code implementations NeurIPS 2020 Chaozheng Wu, Jian Chen, Qiaoyu Cao, Jianchi Zhang, Yunxin Tai, Lin Sun, Kui Jia

To test GPNet, we contribute a synthetic dataset of 6-DOF object grasps; evaluation is conducted using rule-based criteria, simulation test, and real test.

Conditional Automated Channel Pruning for Deep Neural Networks

no code implementations21 Sep 2020 Yixin Liu, Yong Guo, Zichang Liu, Haohua Liu, Jingjie Zhang, Zejun Chen, Jing Liu, Jian Chen

To address this issue, given a target compression rate for the whole model, one can search for the optimal compression rate for each layer.

Model Compression

Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search

1 code implementation ICML 2020 Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan

With the proposed search strategy, our Curriculum Neural Architecture Search (CNAS) method significantly improves the search efficiency and finds better architectures than existing NAS methods.

Neural Architecture Search

Neural encoding and interpretation for high-level visual cortices based on fMRI using image caption features

no code implementations26 Mar 2020 Kai Qiao, Chi Zhang, Jian Chen, Linyuan Wang, Li Tong, Bin Yan

Except for deep network structure, the task or corresponding big dataset is also important for deep network models, but neglected by previous studies.

General Classification Image Classification

BigGAN-based Bayesian reconstruction of natural images from human brain activity

no code implementations13 Mar 2020 Kai Qiao, Jian Chen, Linyuan Wang, Chi Zhang, Li Tong, Bin Yan

In this study, we proposed a new GAN-based Bayesian visual reconstruction method (GAN-BVRM) that includes a classifier to decode categories from fMRI data, a pre-trained conditional generator to generate natural images of specified categories, and a set of encoding models and evaluator to evaluate generated images.

Conditional Image Generation Generative Adversarial Network

Hierarchical Neural Architecture Search for Single Image Super-Resolution

1 code implementation10 Mar 2020 Yong Guo, Yongsheng Luo, Zhenhao He, Jin Huang, Jian Chen

To this end, we design a hierarchical SR search space and propose a hierarchical controller for architecture search.

Image Super-Resolution Neural Architecture Search

Human Gist Processing Augments Deep Learning Breast Cancer Risk Assessment

no code implementations28 Nov 2019 Skylar W. Wurster, Arkadiusz Sitek, Jian Chen, Karla Evans, Gaeun Kim, Jeremy M. Wolfe

Radiologists can classify a mammogram as normal or abnormal at better than chance levels after less than a second's exposure to the images.

BIG-bench Machine Learning

NAT: Neural Architecture Transformer for Accurate and Compact Architectures

1 code implementation NeurIPS 2019 Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang

To verify the effectiveness of the proposed strategies, we apply NAT on both hand-crafted architectures and NAS based architectures.

Neural Architecture Search

Investigating Task-driven Latent Feasibility for Nonconvex Image Modeling

no code implementations18 Oct 2019 Risheng Liu, Pan Mu, Jian Chen, Xin Fan, Zhongxuan Luo

Properly modeling latent image distributions plays an important role in a variety of image-related vision problems.

Deblurring Image Deblurring

Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization

1 code implementation27 Jul 2019 Kai Qiao, Chi Zhang, Jian Chen, Linyuan Wang, Li Tong, Bin Yan

Recently, visual encoding based on functional magnetic resonance imaging (fMRI) have realized many achievements with the rapid development of deep network computation.


Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense

no code implementations12 Apr 2019 Lingyun Jiang, Kai Qiao, Ruoxi Qin, Linyuan Wang, Jian Chen, Haibing Bu, Bin Yan

In image classification of deep learning, adversarial examples where inputs intended to add small magnitude perturbations may mislead deep neural networks (DNNs) to incorrect results, which means DNNs are vulnerable to them.

Adversarial Attack Image Classification

Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis

1 code implementation27 Mar 2019 Yong Guo, Qi Chen, Jian Chen, Qingyao Wu, Qinfeng Shi, Mingkui Tan

To address this issue, we develop a novel GAN called Auto-Embedding Generative Adversarial Network (AEGAN), which simultaneously encodes the global structure features and captures the fine-grained details.

Generative Adversarial Network Image Generation +2

Category decoding of visual stimuli from human brain activity using a bidirectional recurrent neural network to simulate bidirectional information flows in human visual cortices

no code implementations19 Mar 2019 Kai Qiao, Jian Chen, Linyuan Wang, Chi Zhang, Lei Zeng, Li Tong, Bin Yan

Despite the hierarchically similar representations of deep network and human vision, visual information flows from primary visual cortices to high visual cortices and vice versa based on the bottom-up and top-down manners, respectively.

Neurons and Cognition

Deep Learning for Image Super-resolution: A Survey

5 code implementations16 Feb 2019 Zhihao Wang, Jian Chen, Steven C. H. Hoi

Image Super-Resolution (SR) is an important class of image processing techniques to enhance the resolution of images and videos in computer vision.

Image Super-Resolution

Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss

no code implementations19 Sep 2018 Yong Guo, Qi Chen, Jian Chen, Junzhou Huang, Yanwu Xu, JieZhang Cao, Peilin Zhao, Mingkui Tan

However, most deep learning methods employ feed-forward architectures, and thus the dependencies between LR and HR images are not fully exploited, leading to limited learning performance.

Image Super-Resolution

Accurate reconstruction of image stimuli from human fMRI based on the decoding model with capsule network architecture

no code implementations2 Jan 2018 Kai Qiao, Chi Zhang, Linyuan Wang, Bin Yan, Jian Chen, Lei Zeng, Li Tong

We firstly employed the CapsNet to train the nonlinear mapping from image stimuli to high-level capsule features, and from high-level capsule features to image stimuli again in an end-to-end manner.

Open-Ended Question Answering SSIM

Improving Efficiency of SVM k-fold Cross-validation by Alpha Seeding

no code implementations23 Nov 2016 Zeyi Wen, Bin Li, Rao Kotagiri, Jian Chen, Yawen Chen, Rui Zhang

The k-fold cross-validation is commonly used to evaluate the effectiveness of SVMs with the selected hyper-parameters.

The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs

1 code implementation6 Nov 2016 Yong Guo, Jian Chen, Qing Du, Anton Van Den Hengel, Qinfeng Shi, Mingkui Tan

As a result, the representation power of intermediate layers can be very weak and the model becomes very redundant with limited performance.

Model Compression Model Selection

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