A Computer Vision System for Bangladeshi Local Mango Breed Detection using Convolutional Neural Network (CNN) Models

Haque, A S M Farhan Al; Rahman, Md. Riazur; Marouf, Ahmed Al; Khan, Md. Abbas Ali

doi:10.1109/eict48899.2019.9068830

Cited by 9 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The training and testing loss and accuracy values are represented on the vertical axis, while the processing epochs are represented on the horizontal axis. Since the loss and accuracy variation remained consistent after the 60th epoch overtraining the model could lead to an overfitting problem [22]. The training epoch was set to 60 epochs.…”

Section: Training and Benchmarkingmentioning

confidence: 99%

Computer Vision-Based Techniques for Quality Inspection of Concrete Building Structures

Chang¹,

Siu²

2023

Quality Control - An Anthology of Cases

View full text Add to dashboard Cite

Quality performance of building construction is frequently assessed throughout the construction life cycle. In Hong Kong, quality management system must be established before commencing new building works. Regular building inspections are conducted in accordance with the code of practice of new building works. Quality managers are deployed in construction sites to inspect and record any building defects. The concrete cracks must be identified, which is usually followed by proposed rectifications, in order to protect the public and occupants from dangers. This chapter is structured as follows: Background information of concrete cracks is firstly given. Traditional technique of conducting regular manual inspection is introduced, in accordance with Hong Kong’s code of practice “Building Performance Assessment Scoring System (PASS)”. Then, an advanced technique of conducting crack inspection intelligently based on computer vision is introduced. The procedures of defining, training, and benchmarking the architecture of convolutional neural network models are presented. The calculation steps are detailed and illustrated using a simple textbook example. An experiment case study is used to compare the time, cost of inspecting concrete cracks using both manual and advanced technique. The study concludes with a presentation of the future vision of robot-human collaboration for inspecting concrete cracks in building construction.

show abstract

Section: Training and Benchmarkingmentioning

confidence: 99%

Computer Vision-Based Techniques for Quality Inspection of Concrete Building Structures

Chang¹,

Siu²

2023

Quality Control - An Anthology of Cases

View full text Add to dashboard Cite

show abstract

“…Penelitian terdahulu mengenai deep learning menggunakan convolutional neural network sudah banyak dilakukan oleh para peneliti pada berbagai macam objek. Seperti halnya penelitian yang dilakukan oleh peneliti sebelumnya yang menggunakan CNN guna mengklasifikasi motif batik [6].Dari penelitian sebelumnya yaitu pendeteksi jenis mangga di India dikatakan bahwa model CNN dapat mengklasifikasikan di antara berbagai jenis buah mangga dengan kinerja yang sangat memuaskan yaitu nilai AUCROC sebesar 97,3% [7].…”

Section: Metode Penelitianunclassified

Pendiagnosa Daun Mangga Dengan Model Convolutional Neural Network

Ayu

Dwi

Minarno

2021

Com, Engine, Sys, Sci

View full text Add to dashboard Cite

Pertanian adalah salah satu sektor ekonomi yang terpenting di negara-negara Asia Tenggara. Saat ini, pembangunan ekonomi sangat bergantung pada pertanian. Seperti contoh Mangga, Manga juga merupakan bahan makanan yang dapat diolah menjadi berbagai jenis makanan yang lezat. Karena banyaknya manfaat pada buah ini tak jarang masyarakat ingin menanam pohon mangga untuk dibudidayakan dengan tujuan komersil maupun pribadi. Salah satu masalah utama yang menurunkan kualitas dan kuantitas manufaktur pertanian adalah penyakit tanaman. Oleh karena itu bidang penelitian pertanian menarik para peneliti dan ilmuwan untuk memberikan teknik untuk mengidentifikasi penyakit tanaman dengan menggunakan pengolahan gambar dan visi komputer seperti dalam kertas ini yang menggunaka model Convolutional Neural Network (CNN) untuk mengklasifikasi jenis daun mangga yang sakit (terserang hama) dan sehat berdasarkan bentuk dan tekstur daun. Pada penelitian yang dihasilkan tingkat akurasi sebesar 0,96.

show abstract

Classification of Mango Species and Ripeness Using Feature Extraction with an Artificial Neural Network

Hong,

Sariff,

Ismail

et al. 2024

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

A Computer Vision System for Bangladeshi Local Mango Breed Detection using Convolutional Neural Network (CNN) Models

Cited by 9 publications

References 14 publications

Computer Vision-Based Techniques for Quality Inspection of Concrete Building Structures

Computer Vision-Based Techniques for Quality Inspection of Concrete Building Structures

Pendiagnosa Daun Mangga Dengan Model Convolutional Neural Network

Classification of Mango Species and Ripeness Using Feature Extraction with an Artificial Neural Network

Contact Info

Product

Resources

About