Automatic waste classification using deep learning and computer vision techniques

Automatic waste classification using deep learning and computer vision techniques

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Dettagli Bibliografici
Autori principali:	Akash, MD., Shama, Umme Sabiha, Dibash, Dey, Ghosh, Ria
Altri autori:	Karim, Dewan Ziaul
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2023
Soggetti:	Custom CNN Resnet50 VGG16 MobileNetV2 InceptionV3 EfficientNetB0 Pretrained Validation Accuracy Detection Classification YOLOv4 Deep learning YOLOv4-tiny Cognitive learning theory Neural networks (Computer science) Machine learning
Accesso online:	http://hdl.handle.net/10361/21220

Documenti analoghi

Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI
di: Athina, Fahima Hasan, et al.
Pubblicazione: (2022)

A comparative study of lung cancer prediction using deep learning
di: Mugdho, Aka Mohammad, et al.
Pubblicazione: (2023)

Real-time crime detection using convolutional LSTM and YOLOv7
di: Sakiba, Cyrus, et al.
Pubblicazione: (2023)

Analyzing students’ concentration in online courses through Webcam
di: Asif, Md., et al.
Pubblicazione: (2024)

Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
di: Awwal, Alvina, et al.
Pubblicazione: (2021)

Citrus leaf disease detection by image processing
di: Chowdhury, Mahir Faisal, et al.
Pubblicazione: (2024)

An efficient approach for recyclable waste detection and classification using image processing techniques
di: Chowdhury, Prabal Kumar, et al.
Pubblicazione: (2024)

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
di: Rahman, Afridi Ibn, et al.
Pubblicazione: (2022)

Skin disease detection and classification using deep learning
di: Shuvon, Mehedi Hasan, et al.
Pubblicazione: (2022)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
di: Ismail, Sayem Mohammad, et al.
Pubblicazione: (2021)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
di: Hossain, Mohammad Sakib, et al.
Pubblicazione: (2023)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
di: Khan, Farhan Sakib, et al.
Pubblicazione: (2022)

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

A deep learning approach for pneumonia classiﬁcation from chest X-Ray images with ensemble modelling and explainable AI
di: Akhter, Nasrin
Pubblicazione: (2023)

Plant disease diagnosis using deep transfer learning architectures- VGG19, MobileNetV2 and Inception-V3
di: Kobra, Khadija-Tul, et al.
Pubblicazione: (2022)

Skin cancer classification for seven types of skin lesions
di: Rahman, Md. Tawsifur, et al.
Pubblicazione: (2024)

Content based image search in openstack swift
di: Ali Uday, Mir Rownak, et al.
Pubblicazione: (2024)

Fire and disaster detection with multimodal quadcopter By machine learning
di: Afrin, Anika, et al.
Pubblicazione: (2023)

Covid-19 infected lung detection using machine learning
di: Islam, Md. Muntaha, et al.
Pubblicazione: (2022)

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

Identifying brain abnormalities using image processing and CNN models
di: Talukder, Ismat Shehrin, et al.
Pubblicazione: (2021)

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

Explainable breast cancer detection from Histopathology images using transfer learning and XAI
di: Farabi, Farhan, et al.
Pubblicazione: (2023)

Approaching transfer learning to identify correctly worn facial masks
di: Sadid, Tausif, et al.
Pubblicazione: (2021)

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

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

Violent activity detection through surveillance camera using deep learning
di: Miah, Parvez, et al.
Pubblicazione: (2023)

FoodieCal: a convolutional neural network based food detection and calorie estimation system
di: Mashraf, Chowdhury Zerif, et al.
Pubblicazione: (2021)

Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
di: Promita, Samanta Tabassum, et al.
Pubblicazione: (2022)

Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
di: Islam, Tahsin, et al.
Pubblicazione: (2021)

Non-clinical Covid19 diagnosis on CT-scan, Chest X-ray, and respiratory patterns using deep-learning and signal processing
di: Tasnim, Sadia, et al.
Pubblicazione: (2023)

Brain tumor detection with convolutional neural network
di: Galib, Abrar Tahmid, et al.
Pubblicazione: (2024)

An ambient assisted living system for Alzheimer’s patients
di: Abedin, Minhajul, et al.
Pubblicazione: (2023)

An efficient face recognition model using multiple angular images and deep neural network architecture
di: Subah, Silma, et al.
Pubblicazione: (2024)

A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
di: Sarmi, Kaniz Fatima, et al.
Pubblicazione: (2022)

Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection
di: Niaz, H.M, et al.
Pubblicazione: (2024)

Tomato leaf disease detection using Resnet-50 and MobileNet Architecture
di: Tahamid, Abu
Pubblicazione: (2021)

Retinal Diseases Detection using Deep Learning
di: Mashfi, Shahriar, et al.
Pubblicazione: (2023)

Leveraging robust CNN architectures for real-time object recognition from conveyor belt
di: Moon, Nowrin Tasnim, et al.
Pubblicazione: (2023)

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
di: Haque, Samiha, et al.
Pubblicazione: (2021)