Search Results for author: Ling Li

Found 41 papers, 11 papers with code

EdgeConvFormer: Dynamic Graph CNN and Transformer based Anomaly Detection in Multivariate Time Series

no code implementations4 Dec 2023 Jie Liu, Qilin Li, Senjian An, Bradley Ezard, Ling Li

Transformer-based models for anomaly detection in multivariate time series can benefit from the self-attention mechanism due to its advantage in modeling long-term dependencies.

Anomaly Detection Time Series

Pushing the Limits of Machine Design: Automated CPU Design with AI

1 code implementation21 Jun 2023 Shuyao Cheng, Pengwei Jin, Qi Guo, Zidong Du, Rui Zhang, Yunhao Tian, Xing Hu, Yongwei Zhao, Yifan Hao, Xiangtao Guan, Husheng Han, Zhengyue Zhao, Ximing Liu, Ling Li, Xishan Zhang, Yuejie Chu, Weilong Mao, Tianshi Chen, Yunji Chen

By efficiently exploring a search space of unprecedented size 10^{10^{540}}, which is the largest one of all machine-designed objects to our best knowledge, and thus pushing the limits of machine design, our approach generates an industrial-scale RISC-V CPU within only 5 hours.

ALL-E: Aesthetics-guided Low-light Image Enhancement

no code implementations28 Apr 2023 Ling Li, Dong Liang, Yuanhang Gao, Sheng-Jun Huang, Songcan Chen

In this paper, we propose a new paradigm, i. e., aesthetics-guided low-light image enhancement (ALL-E), which introduces aesthetic preferences to LLE and motivates training in a reinforcement learning framework with an aesthetic reward.

Low-Light Image Enhancement valid

Binary stochasticity enabled highly efficient neuromorphic deep learning achieves better-than-software accuracy

no code implementations25 Apr 2023 Yang Li, Wei Wang, Ming Wang, Chunmeng Dou, Zhengyu Ma, Huihui Zhou, Peng Zhang, Nicola Lepri, Xumeng Zhang, Qing Luo, Xiaoxin Xu, Guanhua Yang, Feng Zhang, Ling Li, Daniele Ielmini, Ming Liu

We propose a binary stochastic learning algorithm that modifies all elementary neural network operations, by introducing (i) stochastic binarization of both the forwarding signals and the activation function derivatives, (ii) signed binarization of the backpropagating errors, and (iii) step-wised weight updates.

Binarization

Conceptual Reinforcement Learning for Language-Conditioned Tasks

no code implementations9 Mar 2023 Shaohui Peng, Xing Hu, Rui Zhang, Jiaming Guo, Qi Yi, Ruizhi Chen, Zidong Du, Ling Li, Qi Guo, Yunji Chen

Recently, the language-conditioned policy is proposed to facilitate policy transfer through learning the joint representation of observation and text that catches the compact and invariant information across environments.

reinforcement-learning Reinforcement Learning (RL)

Ultra-low Precision Multiplication-free Training for Deep Neural Networks

no code implementations28 Feb 2023 Chang Liu, Rui Zhang, Xishan Zhang, Yifan Hao, Zidong Du, Xing Hu, Ling Li, Qi Guo

The energy-efficient works try to decrease the precision of multiplication or replace the multiplication with energy-efficient operations such as addition or bitwise shift, to reduce the energy consumption of FP32 multiplications.

Quantization

Towards High Performance One-Stage Human Pose Estimation

no code implementations12 Jan 2023 Ling Li, Lin Zhao, Linhao Xu, Jie Xu

Making top-down human pose estimation method present both good performance and high efficiency is appealing.

Human Detection Keypoint Detection +1

Biomedical image analysis competitions: The state of current participation practice

no code implementations16 Dec 2022 Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Patrick Godau, Veronika Cheplygina, Michal Kozubek, Sharib Ali, Anubha Gupta, Jan Kybic, Alison Noble, Carlos Ortiz de Solórzano, Samiksha Pachade, Caroline Petitjean, Daniel Sage, Donglai Wei, Elizabeth Wilden, Deepak Alapatt, Vincent Andrearczyk, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Vivek Singh Bawa, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Jinwook Choi, Olivier Commowick, Marie Daum, Adrien Depeursinge, Reuben Dorent, Jan Egger, Hannah Eichhorn, Sandy Engelhardt, Melanie Ganz, Gabriel Girard, Lasse Hansen, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Hyunjeong Kim, Bennett Landman, Hongwei Bran Li, Jianning Li, Jun Ma, Anne Martel, Carlos Martín-Isla, Bjoern Menze, Chinedu Innocent Nwoye, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Carole Sudre, Kimberlin Van Wijnen, Armine Vardazaryan, Tom Vercauteren, Martin Wagner, Chuanbo Wang, Moi Hoon Yap, Zeyun Yu, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Rina Bao, Chanyeol Choi, Andrew Cohen, Oleh Dzyubachyk, Adrian Galdran, Tianyuan Gan, Tianqi Guo, Pradyumna Gupta, Mahmood Haithami, Edward Ho, Ikbeom Jang, Zhili Li, Zhengbo Luo, Filip Lux, Sokratis Makrogiannis, Dominik Müller, Young-tack Oh, Subeen Pang, Constantin Pape, Gorkem Polat, Charlotte Rosalie Reed, Kanghyun Ryu, Tim Scherr, Vajira Thambawita, Haoyu Wang, Xinliang Wang, Kele Xu, Hung Yeh, Doyeob Yeo, Yixuan Yuan, Yan Zeng, Xin Zhao, Julian Abbing, Jannes Adam, Nagesh Adluru, Niklas Agethen, Salman Ahmed, Yasmina Al Khalil, Mireia Alenyà, Esa Alhoniemi, Chengyang An, Talha Anwar, Tewodros Weldebirhan Arega, Netanell Avisdris, Dogu Baran Aydogan, Yingbin Bai, Maria Baldeon Calisto, Berke Doga Basaran, Marcel Beetz, Cheng Bian, Hao Bian, Kevin Blansit, Louise Bloch, Robert Bohnsack, Sara Bosticardo, Jack Breen, Mikael Brudfors, Raphael Brüngel, Mariano Cabezas, Alberto Cacciola, Zhiwei Chen, Yucong Chen, Daniel Tianming Chen, Minjeong Cho, Min-Kook Choi, Chuantao Xie Chuantao Xie, Dana Cobzas, Julien Cohen-Adad, Jorge Corral Acero, Sujit Kumar Das, Marcela de Oliveira, Hanqiu Deng, Guiming Dong, Lars Doorenbos, Cory Efird, Sergio Escalera, Di Fan, Mehdi Fatan Serj, Alexandre Fenneteau, Lucas Fidon, Patryk Filipiak, René Finzel, Nuno R. Freitas, Christoph M. Friedrich, Mitchell Fulton, Finn Gaida, Francesco Galati, Christoforos Galazis, Chang Hee Gan, Zheyao Gao, Shengbo Gao, Matej Gazda, Beerend Gerats, Neil Getty, Adam Gibicar, Ryan Gifford, Sajan Gohil, Maria Grammatikopoulou, Daniel Grzech, Orhun Güley, Timo Günnemann, Chunxu Guo, Sylvain Guy, Heonjin Ha, Luyi Han, Il Song Han, Ali Hatamizadeh, Tian He, Jimin Heo, Sebastian Hitziger, SeulGi Hong, Seungbum Hong, Rian Huang, Ziyan Huang, Markus Huellebrand, Stephan Huschauer, Mustaffa Hussain, Tomoo Inubushi, Ece Isik Polat, Mojtaba Jafaritadi, SeongHun Jeong, Bailiang Jian, Yuanhong Jiang, Zhifan Jiang, Yueming Jin, Smriti Joshi, Abdolrahim Kadkhodamohammadi, Reda Abdellah Kamraoui, Inha Kang, Junghwa Kang, Davood Karimi, April Khademi, Muhammad Irfan Khan, Suleiman A. Khan, Rishab Khantwal, Kwang-Ju Kim, Timothy Kline, Satoshi Kondo, Elina Kontio, Adrian Krenzer, Artem Kroviakov, Hugo Kuijf, Satyadwyoom Kumar, Francesco La Rosa, Abhi Lad, Doohee Lee, Minho Lee, Chiara Lena, Hao Li, Ling Li, Xingyu Li, Fuyuan Liao, Kuanlun Liao, Arlindo Limede Oliveira, Chaonan Lin, Shan Lin, Akis Linardos, Marius George Linguraru, Han Liu, Tao Liu, Di Liu, Yanling Liu, João Lourenço-Silva, Jingpei Lu, Jiangshan Lu, Imanol Luengo, Christina B. Lund, Huan Minh Luu, Yi Lv, Uzay Macar, Leon Maechler, Sina Mansour L., Kenji Marshall, Moona Mazher, Richard McKinley, Alfonso Medela, Felix Meissen, Mingyuan Meng, Dylan Miller, Seyed Hossein Mirjahanmardi, Arnab Mishra, Samir Mitha, Hassan Mohy-ud-Din, Tony Chi Wing Mok, Gowtham Krishnan Murugesan, Enamundram Naga Karthik, Sahil Nalawade, Jakub Nalepa, Mohamed Naser, Ramin Nateghi, Hammad Naveed, Quang-Minh Nguyen, Cuong Nguyen Quoc, Brennan Nichyporuk, Bruno Oliveira, David Owen, Jimut Bahan Pal, Junwen Pan, Wentao Pan, Winnie Pang, Bogyu Park, Vivek Pawar, Kamlesh Pawar, Michael Peven, Lena Philipp, Tomasz Pieciak, Szymon Plotka, Marcel Plutat, Fattaneh Pourakpour, Domen Preložnik, Kumaradevan Punithakumar, Abdul Qayyum, Sandro Queirós, Arman Rahmim, Salar Razavi, Jintao Ren, Mina Rezaei, Jonathan Adam Rico, ZunHyan Rieu, Markus Rink, Johannes Roth, Yusely Ruiz-Gonzalez, Numan Saeed, Anindo Saha, Mostafa Salem, Ricardo Sanchez-Matilla, Kurt Schilling, Wei Shao, Zhiqiang Shen, Ruize Shi, Pengcheng Shi, Daniel Sobotka, Théodore Soulier, Bella Specktor Fadida, Danail Stoyanov, Timothy Sum Hon Mun, Xiaowu Sun, Rong Tao, Franz Thaler, Antoine Théberge, Felix Thielke, Helena Torres, Kareem A. Wahid, Jiacheng Wang, Yifei Wang, Wei Wang, Xiong Wang, Jianhui Wen, Ning Wen, Marek Wodzinski, Ye Wu, Fangfang Xia, Tianqi Xiang, Chen Xiaofei, Lizhan Xu, Tingting Xue, Yuxuan Yang, Lin Yang, Kai Yao, Huifeng Yao, Amirsaeed Yazdani, Michael Yip, Hwanseung Yoo, Fereshteh Yousefirizi, Shunkai Yu, Lei Yu, Jonathan Zamora, Ramy Ashraf Zeineldin, Dewen Zeng, Jianpeng Zhang, Bokai Zhang, Jiapeng Zhang, Fan Zhang, Huahong Zhang, Zhongchen Zhao, Zixuan Zhao, Jiachen Zhao, Can Zhao, Qingshuo Zheng, Yuheng Zhi, Ziqi Zhou, Baosheng Zou, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

Of these, 84% were based on standard architectures.

Benchmarking

Causality-driven Hierarchical Structure Discovery for Reinforcement Learning

no code implementations13 Oct 2022 Shaohui Peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo, Qi Yi, Ruizhi Chen, Xishan Zhang, Zidong Du, Ling Li, Qi Guo, Yunji Chen

To address this issue, we propose CDHRL, a causality-driven hierarchical reinforcement learning framework, leveraging a causality-driven discovery instead of a randomness-driven exploration to effectively build high-quality hierarchical structures in complicated environments.

Hierarchical Reinforcement Learning reinforcement-learning +1

SaiT: Sparse Vision Transformers through Adaptive Token Pruning

1 code implementation11 Oct 2022 Ling Li, David Thorsley, Joseph Hassoun

Sparse adaptive image Transformer (SaiT) offers varying levels of model acceleration by merely changing the token sparsity on the fly.

Knowledge Distillation

MaiT: Leverage Attention Masks for More Efficient Image Transformers

no code implementations6 Jul 2022 Ling Li, Ali Shafiee Ardestani, Joseph Hassoun

Though image transformers have shown competitive results with convolutional neural networks in computer vision tasks, lacking inductive biases such as locality still poses problems in terms of model efficiency especially for embedded applications.

Automatic Facial Skin Feature Detection for Everyone

no code implementations30 Mar 2022 Qian Zheng, Ankur Purwar, Heng Zhao, Guang Liang Lim, Ling Li, Debasish Behera, Qian Wang, Min Tan, Rizhao Cai, Jennifer Werner, Dennis Sng, Maurice van Steensel, Weisi Lin, Alex C Kot

We present an automatic facial skin feature detection method that works across a variety of skin tones and age groups for selfies in the wild.

Product Recommendation

Semantically Contrastive Learning for Low-light Image Enhancement

1 code implementation13 Dec 2021 Dong Liang, Ling Li, Mingqiang Wei, Shuo Yang, Liyan Zhang, Wenhan Yang, Yun Du, Huiyu Zhou

Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images.

Contrastive Learning Low-Light Image Enhancement +1

MaiT: integrating spatial locality into image transformers with attention masks

1 code implementation29 Sep 2021 Ling Li, Ali Shafiee, Joseph H Hassoun

Moreover, attention masks regulate the training of attention maps, which facilitates the convergence and improves the accuracy of deeper transformers.

Deep learning based low-dose synchrotron radiation CT reconstruction

no code implementations9 Jun 2021 Ling Li, Yu Hu

Synchrotron radiation sources are widely used in various fields, among which computed tomography (CT) is one of the most important.

Computed Tomography (CT)

Active Terahertz Imaging Dataset for Concealed Object Detection

1 code implementation8 May 2021 Dong Liang, Fei Xue, Ling Li

Concealed object detection in Terahertz imaging is an urgent need for public security and counter-terrorism.

Object object-detection +1

Product semantics translation from brain activity via adversarial learning

no code implementations29 Mar 2021 Pan Wang, Zhifeng Gong, Shuo Wang, Hao Dong, Jialu Fan, Ling Li, Peter Childs, Yike Guo

To modify a design semantic of a given product from personalised brain activity via adversarial learning, in this work, we propose a deep generative transformation model to modify product semantics from the brain signal.

EEG Electroencephalogram (EEG) +1

Verifying Design through Generative Visualization of Neural Activities

no code implementations28 Mar 2021 Pan Wang, Danlin Peng, Simiao Yu, Chao Wu, Peter Childs, Yike Guo, Ling Li

A recurrent neural network is used as the encoder to learn latent representation from electroencephalogram (EEG) signals, recorded while subjects looked at 50 categories of images.

EEG Electroencephalogram (EEG) +1

A General Framework for Revealing Human Mind with auto-encoding GANs

no code implementations10 Feb 2021 Pan Wang, Rui Zhou, Shuo Wang, Ling Li, Wenjia Bai, Jialu Fan, Chunlin Li, Peter Childs, Yike Guo

For this reason, we propose an end-to-end brain decoding framework which translates brain activity into an image by latent space alignment.

Brain Decoding

Causal Factors, Benefits and Challenges of Test-Driven Development: Practitioner Perceptions

no code implementations29 Jan 2021 Jim Buchan, Ling Li, Stephen G. MacDonell

This report describes the experiences of one organization's adoption of Test Driven Development (TDD) practices as part of a medium-term software project employing Extreme Programming as a methodology.

Software Engineering

Conditional Local Convolution for Spatio-temporal Meteorological Forecasting

1 code implementation4 Jan 2021 Haitao Lin, Zhangyang Gao, Yongjie Xu, Lirong Wu, Ling Li, Stan. Z. Li

We further propose the distance and orientation scaling terms to reduce the impacts of irregular spatial distribution.

Spatio-Temporal Forecasting Weather Forecasting

Structured Context Enhancement Network for Mouse Pose Estimation

1 code implementation1 Dec 2020 Feixiang Zhou, Zheheng Jiang, Zhihua Liu, Fang Chen, Long Chen, Lei Tong, Zhile Yang, Haikuan Wang, Minrui Fei, Ling Li, Huiyu Zhou

However, quantifying mouse behaviours from videos or images remains a challenging problem, where pose estimation plays an important role in describing mouse behaviours.

Animal Pose Estimation

Muti-view Mouse Social Behaviour Recognition with Deep Graphical Model

1 code implementation4 Nov 2020 Zheheng Jiang, Feixiang Zhou, Aite Zhao, Xin Li, Ling Li, DaCheng Tao, Xuelong Li, Huiyu Zhou

To address this problem, we here propose a novel multiview latent-attention and dynamic discriminative model that jointly learns view-specific and view-shared sub-structures, where the former captures unique dynamics of each view whilst the latter encodes the interaction between the views.

CANet: Context Aware Network for 3D Brain Glioma Segmentation

1 code implementation15 Jul 2020 Zhihua Liu, Lei Tong, Long Chen, Feixiang Zhou, Zheheng Jiang, Qianni Zhang, Yinhai Wang, Caifeng Shan, Ling Li, Huiyu Zhou

Automated segmentation of brain glioma plays an active role in diagnosis decision, progression monitoring and surgery planning.

Brain Tumor Segmentation Segmentation +1

Regularizing Semi-supervised Graph Convolutional Networks with a Manifold Smoothness Loss

no code implementations11 Feb 2020 Qilin Li, Wanquan Liu, Ling Li

Existing graph convolutional networks focus on the neighborhood aggregation scheme.

A Comparison and Strategy of Semantic Segmentation on Remote Sensing Images

no code implementations24 May 2019 Junxing Hu, Ling Li, Yijun Lin, Fengge Wu, Junsuo Zhao

But a large number of useless raw images, limited data storage resource and poor transmission capability on satellites hinder our use of valuable images.

Segmentation Semantic Segmentation

A Research and Strategy of Remote Sensing Image Denoising Algorithms

no code implementations24 May 2019 Ling Li, Junxing Hu, Fengge Wu, Junsuo Zhao

Most raw data download from satellites are useless, resulting in transmission waste, one solution is to process data directly on satellites, then only transmit the processed results to the ground.

Image Denoising

A Fully-Automatic Framework for Parkinson's Disease Diagnosis by Multi-Modality Images

no code implementations26 Feb 2019 Jiahang Xu, Fangyang Jiao, Yechong Huang, Xinzhe Luo, Qian Xu, Ling Li, Xueling Liu, Chuantao Zuo, Ping Wu, Xiahai Zhuang

Methods: In this paper, we proposed an automatic, end-to-end, multi-modality diagnosis framework, including segmentation, registration, feature generation and machine learning, to process the information of the striatum for the diagnosis of PD.

General Classification Segmentation

A Novel Euler's Elastica based Segmentation Approach for Noisy Images via using the Progressive Hedging Algorithm

no code implementations20 Feb 2019 Lu Tan, Ling Li, Wanquan Liu, Jie Sun, Min Zhang

Euler's Elastica based unsupervised segmentation models have strong capability of completing the missing boundaries for existing objects in a clean image, but they are not working well for noisy images.

Segmentation

Semi-supervised Learning on Graph with an Alternating Diffusion Process

no code implementations16 Feb 2019 Qilin Li, Senjian An, Ling Li, Wanquan Liu

Graph-based semi-supervised learning usually involves two separate stages, constructing an affinity graph and then propagating labels for transductive inference on the graph.

graph construction

Robust X-ray Sparse-view Phase Tomography via Hierarchical Synthesis Convolutional Neural Networks

no code implementations30 Jan 2019 Ziling Wu, Abdulaziz Alorf, Ting Yang, Ling Li, Yunhui Zhu

In this paper, we report a robust hierarchical synthesis reconstruction approach, where training data is pre-processed to separate the information on the domains where sampling biases are suspected.

Computed Tomography (CT) Image Reconstruction

Sparse Subspace Clustering via Diffusion Process

no code implementations5 Aug 2016 Qilin Li, Ling Li, Wanquan Liu

Subspace clustering refers to the problem of clustering high-dimensional data that lie in a union of low-dimensional subspaces.

Clustering

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