Deep Learning-Based Longitudinal Prediction of Childhood Myopia Progression Using Fundus Image Sequences and Baseline Refraction Data

no code implementations • 31 Jul 2024 • Mengtian Kang, Yansong Hu, Shuo Gao, Yuanyuan Liu, Hongbei Meng, Xuemeng Li, Xuhang Chen, Hubin Zhao, Jing Fu, Guohua Hu, Wei Wang, Yanning Dai, Arokia Nathan, Peter Smielewski, Ningli Wang, Shiming Li

In this study, we introduce a novel, high-accuracy method for quantitatively predicting the myopic trajectory and myopia risk in children using only fundus images and baseline refraction data.

Lightweight, error-tolerant edge detection using memristor-enabled stochastic logics

no code implementations • 25 Feb 2024 • Lekai Song, Pengyu Liu, Jingfang Pei, Yang Liu, Songwei Liu, Shengbo Wang, Leonard W. T. Ng, Tawfique Hasan, Kong-Pang Pun, Shuo Gao, Guohua Hu

The demand for efficient edge vision has spurred the interest in developing stochastic computing approaches for performing image processing tasks.

Autonomous Driving Edge Detection +1

Intelligent machines work in unstructured environments by differential neuromorphic computing

no code implementations • 16 Sep 2023 • Shengbo Wang, Shuo Gao, Chenyu Tang, Edoardo Occhipinti, Cong Li, Shurui Wang, Jiaqi Wang, Hubin Zhao, Guohua Hu, Arokia Nathan, Ravinder Dahiya, Luigi Occhipinti

By mimicking the intrinsic nature of human low-level perception mechanisms, the electronic memristive neuromorphic circuit-based method, presented here shows the potential for adapting to diverse sensing technologies and helping intelligent machines generate smart high-level decisions in the real world.

Autonomous Driving Decision Making