Pest detection system using machine learning techniques

Pest detection system using machine learning techniques

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022

Bibliographic Details
Main Authors:	Prithvi, Protyusha Barua, Zahin, Fabliha, Anny, Sanjida Sultana
Other Authors:	Chakrabarty, Amitabha
Format:	Thesis
Language:	English
Published:	Brac University 2022
Subjects:	Deep learning Transfer learning Pest detection Data augmentation Loss function Hyperparameter tuning Support Vector Machine (SVM) Inceptionv3 Xception You Only Look Once version 5 (YOLOv5) Convolutional Neural Network (CNN) Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science)
Online Access:	http://hdl.handle.net/10361/17127

Similar Items

Classifying insect pests from image data using deep learning
by: Mohsin, Md. Raiyan Bin, et al.
Published: (2022)

Recognising license plate from image data using deep learning
by: Golder, Rupam, et al.
Published: (2023)

Diabetic retinopathy detection and classification by using deep learning
by: Hossain, Shahriar, et al.
Published: (2022)

Deep learning-based real-time pothole detection for avoiding road accident
by: Basher, Rafsan, et al.
Published: (2022)

An efficient deep learning approach to classify white blood cells
by: Turja, Afif Ibna Kadir Khan, et al.
Published: (2024)

An efficient deep learning approach to detect skin Cancer
by: Islam, Ashfaqul, et al.
Published: (2022)

Corn leaf disease detection using deep convolution neural network
by: Rabbi, Rawhatur, et al.
Published: (2023)

Document template identification and data extraction using machine learning and deep learning approach
by: Roy, Kaushik, et al.
Published: (2024)

Visual object classification from fMRI data
by: Newaz, Syed Mishar, et al.
Published: (2022)

An efficient ML approach to detect brain tumor using MRI images
by: Muktadir, MD. Arafat, et al.
Published: (2024)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
by: Islam, Roman, et al.
Published: (2024)

Occluded object detection for autonomous vehicles employing YOLOv5, YOLOX and Faster R-CNN
by: Mostafa, Tanzim, et al.
Published: (2022)

Finding location-specific aggregated air quality index with smartphone images using deep convolutional neural network
by: Mondal, Joyanta Jyoti, et al.
Published: (2023)

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

A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium
by: Ahmed, Istiak, et al.
Published: (2023)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
by: Sakir, Adnan, et al.
Published: (2023)

Density based traffic control system for a four way intersection
by: Chowdhury, Faizul Bari, et al.
Published: (2024)

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

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

Prostate cancer detection using deep learning neural network with transfer learning approach
by: Badhon, Ariful Islam Mahmud, et al.
Published: (2022)

An efficient deep learning approach to detect skin cancer using image data
by: Chowdhury, Yaser Al Rahman, et al.
Published: (2023)

Performance analysis of stacking neural network and machine learning model for detecting fraudulent transaction
by: Chowdhury, Ahnaf Shahriyar, et al.
Published: (2021)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
by: Toufique, S.M, et al.
Published: (2024)

ProteoKnight: phage virion protein classification with CNN and uncertainty quantification
by: Bhuiyan, Abir Ahammed, et al.
Published: (2024)

Application of CNN based architectures in detection of distracted drivers
by: Arafin, Irfana, et al.
Published: (2023)

Leveraging sequential deep learning models for detecting multitude of human action categories
by: Pranta, Kazi Al Refat, et al.
Published: (2024)

Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
by: Hasan, M. M. Kamrul, et al.
Published: (2022)

Intracranial hemorrhage detection using CNN-LSTM fusion model
by: Ahmed, Kazi sabab, et al.
Published: (2022)

Visual object recognition using deep convolutional neural network
by: Ahmed, Sabbir
Published: (2017)

Classification of peripheral blood cell images using deep learning
by: Aadi, Oyshik Ahmed, et al.
Published: (2024)

Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network
by: Rayhan, Mohammad, et al.
Published: (2020)

Fighting depression: psychological approaches among Bangladeshi university students
by: Sen, Sanjib Kumar, et al.
Published: (2022)

A modern technique to detect potholes by Computer Vision and Deep Learning
by: Saif, Muntasir Mahmud, et al.
Published: (2023)

Detection of handwritten text using convolutional neural network
by: Jasim, Rabib Bin, et al.
Published: (2024)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
by: Alhossen, Md., et al.
Published: (2021)

Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
by: Fahim, Kaji Mehedi Hasan, et al.
Published: (2024)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
by: Shahriar, Hasan, et al.
Published: (2022)

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

Classification of retinal diseases from OCT images using deep learning models
by: Mokarrom, Md Saif, et al.
Published: (2024)

Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques
by: Ahasan, Md. Mubtasim, et al.
Published: (2022)