papers

Publications (22)

cs.LG2019

EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction

Nana Wang, Li Cui, Xi Huang +3

The precise diagnosis is of great significance in developing precise treatment plans to restore neck function and reduce the burden posed by the cervical spondylosis (CS). However,…

cs.LG2018

EasiCSDeep: A deep learning model for Cervical Spondylosis Identification using surface electromyography signal

Nana Wang, Li Cui, Xi Huang +2

Cervical spondylosis (CS) is a common chronic disease that affects up to two-thirds of the population and poses a serious burden on individuals and society. The early identificatio…

cs.LG2026

Deep Neural Networks Inspired by Differential Equations

Yongshuai Liu, Lianfang Wang, Kuilin Qin +6

Deep learning has become a pivotal technology in fields such as computer vision, scientific computing, and dynamical systems, significantly advancing these disciplines. However, ne…

cs.CV2020

Volume Preserving Image Segmentation with Entropic Regularization Optimal Transport and Its Applications in Deep Learning

Haifeng Li, Jun Liu, Li Cui +2

Image segmentation with a volume constraint is an important prior for many real applications. In this work, we present a novel volume preserving image segmentation algorithm, which…

cs.CV2025

NF-SLAM: Effective, Normalizing Flow-supported Neural Field representations for object-level visual SLAM in automotive applications

Li Cui, Yang Ding, Richard Hartley +3

We propose a novel, vision-only object-level SLAM framework for automotive applications representing 3D shapes by implicit signed distance functions. Our key innovation consists of…

cs.CV2020

Background Learnable Cascade for Zero-Shot Object Detection

Ye Zheng, Ruoran Huang, Chuanqi Han +2

Zero-shot detection (ZSD) is crucial to large-scale object detection with the aim of simultaneously localizing and recognizing unseen objects. There remain several challenges for Z…