A Study on Image Recognition of Chinese Herbal Medicine Based on Probabilistic Convolution Voting Model

This study investigates the application of deep learning in the field of Chinese herbal medicine (CHM) image recognition, proposing a novel multi-model ensemble approach called the Probabilistic Convolution Voting Model (PCVM) to address the limitations of current single-model systems. Traditional C

Authors

Ziting Gao
Yiheng Yan

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.4108/eai.21-11-2024.2354590
Primary Topic: Traditional Chinese Medicine Studies
Type: article
Field-Weighted Citation Impact: 0.00

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article

A Study on Image Recognition of Chinese Herbal Medicine Based on Probabilistic Convolution Voting Model

Ziting Gao, Yiheng Yan

Jan 1, 2025

Traditional Chinese Medicine Studies

article

A Study on Image Recognition of Chinese Herbal Medicine Based on Probabilistic Convolution Voting Model

Ziting Gao, Yiheng Yan

January 1, 2025article en

Abstract

Gender equality

Openalex Percentile: Top 92%

Traditional Chinese Medicine Studies

DOI Open Access PDF OpenAlex

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A Study on Image Recognition of Chinese Herbal Medicine Based on Probabilistic Convolution Voting Model — Ziting Gao, Yiheng Yan · (2025) | TGRS Research Map | TGRS