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.

Xehetasun bibliografikoak
Egile Nagusiak:	Niloy, Mahir Ahmed, Bhowmik, Tanmay, Abedin, Jennifer, Ferdous, Syeda Jannatul, Jahan, Ishrat
Beste egile batzuk:	Noor, Jannatun
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Livestock disease Disease detection Neural network Ensemble model Gradient boosting classifier Machine learning Neural networks (Computer science). Livestock > Diseases. Deep learning.
Sarrera elektronikoa:	http://hdl.handle.net/10361/24268

Antzeko izenburuak

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

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

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

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

Agriculture and livestock programme
nork: Ahmed, Tanvir
Argitaratua: (2016)

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

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

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

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

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

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

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

Early detection of chronic kidney disease using machine learning
nork: Abrar, Tahmid, et al.
Argitaratua: (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
nork: Hasib, Mehadi Hasan, et al.
Argitaratua: (2021)

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

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

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

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

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

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

Deep learning based early Glaucoma detection
nork: Islam, Aabrar, et al.
Argitaratua: (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
nork: Palok, Tanvir Ahmed, et al.
Argitaratua: (2024)

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

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

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

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

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

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

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

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

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

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

PlantGuard: intelligent plant disease detection
nork: Khanom, Nazifa
Argitaratua: (2024)

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

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

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

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

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