深度学习技术与应用大作业，Kaggle植物分类，Peking University

Kaggle Competition Project as well as ANLY 590 Final Project. Task: Determine the species of a seedling from an image

classify plant seedling into weed seedling and crop seedling using CNN

Plant Seedlings Classification from kaggle competition

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Plant seedlings classification with a CNN

Built a robust image classifier using CNNs to efficiently classify different plant seedlings and weeds to improve crop yields and minimize human involvement.

A basic classifier for the Kaggle Contest, "Plant Seedlings Classification" in Keras.

植物幼苗识别

Kaggle Competition: https://kaggle.com/c/plant-seedlings-classification

By using the convolutional neural network (CNN) to classify the plant seedling with the support of Keras libraries

Determine a seedling Species from an image based on Kaggle Competition

The code and submissions for the Kaggle Plant Seedling Classification Challenge

Kaggle competition for plant seedlings classification.

Kaggle competition of 'Plant Seedlings Classification'

Kaggle | Plant Seedlings Classification

参与Kaggle上的plant seeding classification的比赛，利用传统的图像特征提取方法以及传统机器学习达到78%的准确率

kaggle competition, top 6% (47th of 836)

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Image Classification with ResNet50, Docker, and Streamlit

It has 12 Classes for twelve different types of crops. This Dataset is in a zip file containing twelve folders of each plant containing their pictures. It is a Image Classification Problem, which can be easily solved Deep Learning Models such CNN(Convolutional Neural Networks)

基于SVM的Plant Seedlings Classification植物分类

CZ4041 Project

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Plant Seedlings Classification

EfficientNet

A CNN-based image classifier to distinguish crop seedlings from weeds, optimized with data augmentation and learning rate tuning. Developed for precision agriculture applications, this project demonstrates computer vision techniques for automated crop/weed detection.

using neural network made one predictive model that predict the seedling done in plant from 12 species present in it.

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