Exploring machine learning techniques for symptom-based detection of livestock diseases

Exploring machine learning techniques for symptom-based detection of livestock diseases

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.

Dettagli Bibliografici
Autori principali:	Niloy, Mahir Ahmed, Bhowmik, Tanmay, Abedin, Jennifer, Ferdous, Syeda Jannatul, Jahan, Ishrat
Altri autori:	Noor, Jannatun
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2024
Soggetti:	Livestock disease Disease detection Neural network Ensemble model Gradient boosting classifier Machine learning Neural networks (Computer science). Livestock > Diseases. Deep learning.
Accesso online:	http://hdl.handle.net/10361/24268

Documenti analoghi

Use of machine learning and IoT for monitoring and tracking of livestock
di: Aunindita, Rudaba Farhin, et al.
Pubblicazione: (2023)

Application of machine learning techniques on the context of livestock analysis
di: Islam, Md. Shajedul, et al.
Pubblicazione: (2018)

Livestock resources in Bangladesh : present status and future potential /
di: Ālama, Jāhāṅgīra
Pubblicazione: (1995)

Real-time mastitis detection in livestock using deep learning and machine learning leveraging edge devices
di: Ghosh, Kawshik Kumar, et al.
Pubblicazione: (2023)

Agriculture and livestock programme
di: Ahmed, Tanvir
Pubblicazione: (2016)

X-Ray classification to detect COVID-19 using ensemble model
di: Solaiman, Ishmam Ahmed, et al.
Pubblicazione: (2021)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
di: Shawan, Naveed Rahman, et al.
Pubblicazione: (2019)

Detecting online recruitment fraud by using machine learning
di: Ghosh, Gitanjali, et al.
Pubblicazione: (2021)

Association between household livestock ownership and childhood stunting in Bangladesh – A spatial analysis
di: Hossain, Md. Belal, et al.
Pubblicazione: (2022)

The activities of accounts and finance department of the dairy and livestock program of SOJAG
di: Matin, Yusuf Ibn
Pubblicazione: (2019)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
di: Ferdous, Md.Rubaiat, et al.
Pubblicazione: (2024)

An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
di: Bhuiyan, Mahdi Hasan, et al.
Pubblicazione: (2024)

Early detection of chronic kidney disease using machine learning
di: Abrar, Tahmid, et al.
Pubblicazione: (2019)

Maximum livestock production from minimum land : proceedings of the fourth seminar held from 2nd to 5th of February 1981 at the Bangladesh Agricultural University, Mymensingh Bangladesh /

Efficient image processing and machine learning approach for predicting retinal diseases
di: Hasib, Mehadi Hasan, et al.
Pubblicazione: (2021)

Plant leaf disease identification
di: Hasan Mahin, Mohammad Rakibul, et al.
Pubblicazione: (2024)

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
di: Turjo, Aquib Abtahi, et al.
Pubblicazione: (2021)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
di: Ifty, Md. Hasin Sarwar, et al.
Pubblicazione: (2024)

A deep learning approach for prediction of ADHD using brain structure
di: Siam, Shafin Ahad, et al.
Pubblicazione: (2024)

Smallholder livestock development project Bangladesh: third misssion report, phase IV
di: BRAC
Pubblicazione: (2016)

Building a credit scoring model to assign a reference score based on credit transaction and relevant profile data
di: Islam, Saqib Al, et al.
Pubblicazione: (2020)

Deep learning based early Glaucoma detection
di: Islam, Aabrar, et al.
Pubblicazione: (2024)

Maximum livestock production from minimum land : proceedings of the third seminar, held from 13th to 18th February 1982 at Bangladesh Agricultural Research Institute, Joydebpur /

Medical image reader powered by artificial intelligence
di: Palok, Tanvir Ahmed, et al.
Pubblicazione: (2024)

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
di: Datta, Nirjhor, et al.
Pubblicazione: (2024)

Center for self riliance : a place for learning and sharing
di: Arefin, Md. Abrarul
Pubblicazione: (2018)

Plant disease detection using convolutional neural network
di: Hossain, Mohammad Shifat, et al.
Pubblicazione: (2021)

An eﬃcient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
di: Sagor, Mostofa Kamal, et al.
Pubblicazione: (2021)

Predicting Novel Coronavirus (nCoV) strains detecting the mutation process applying neural networking
di: Rafi, Abdullah Hasan Sajjad, et al.
Pubblicazione: (2024)

Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
di: Shahriar, Farhan, et al.
Pubblicazione: (2021)

Detection of early stages of Parkinson's disease by analyzing fMRI data and machine learning approaches
di: Neehal, Ahmed Hasin, et al.
Pubblicazione: (2020)

Tomato leaf disease detection using convolutional neural network
di: Hasan, Md. Riazul, et al.
Pubblicazione: (2023)

Thoracic complication detection on chest X-rays using deep learning
di: Ratul, Rizwanul Hoque, et al.
Pubblicazione: (2021)

An early assessment of CFPR II support packages
di: Das, Narayan Chandra, et al.
Pubblicazione: (2022)

PlantGuard: intelligent plant disease detection
di: Khanom, Nazifa
Pubblicazione: (2024)

Heart disease prediction system
di: Amit, Tayab Al Azad, et al.
Pubblicazione: (2022)

Prediction on large scale data using extreme gradient boosting
di: Sawon, Md.Tariq Hasan, et al.
Pubblicazione: (2016)

Heart disease prediction using machine learning algorithms
di: Ali, Musfiq, et al.
Pubblicazione: (2019)

Comparative study of X-ray and CT scan images for the detection of COVID-19 using deep learning
di: Niloy, Ahashan Habib, et al.
Pubblicazione: (2021)

Early detection of parkinson’s disease using image processing and artificial neural network
di: Rumman, Mosarrat, et al.
Pubblicazione: (2018)