Browsing by Subject "VGG16"
Now showing items 1-20 of 30
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Automatic waste classification using deep learning and computer vision techniques
(Brac University, 2023-03)Waste management refers to a system that starts with classifying different kinds of waste and gradually managing it from its inception to its final disposal. Labeling waste in a proper manner can ensure the best outcome ... -
Bone age comparison using convolutional neural network
(BRAC University, 2019-04)In the last few years,Machine Learning has taken the world by storm. From predictive web browsing to the email and text classi cation,from the autonomous car to facial recognition, machine learning is the main core of ... -
CancerCare: A reliable and secured self-supervising and interactive system using deep learning
(Brac University, 2023-01)Cancer is the ultimate global health issue in the 21st century, as its burden is in creasing day by day. In the year 2020 [36], 18.1 million cancer cases were estimated, where 9.3 million were men and 8.8 million were ... -
Cassava leaf disease classification using deep learning and convolutional neural network ensemble
(Brac University, 2022-01)Cassava is a high-protein and nutrient-dense plant, notably inside the leaves. Cassava is often used as a rice alternative. Pests, viruses, bacteria, and fungus may cause a variety of illnesses on cassava leaves. This ... -
Classification of Shot Selection by Batsman in Cricket Matches Using Deep Neural Network
(Brac University, 2022-05)Machine learning (ML) is such a field that focuses on learning based method. It basically leverage data to improve the performance on particular tasks. It creates a model based on training data and makes prediction ... -
Comparative analysis of machine learning techniques in optimal site selection
(Brac University, 2023-01)Site selection is a crucial aspect of many businesses, as a company’s location can sig nificantly impact its success. In recent years, machine learning techniques have been increasingly used to assist with optimal site ... -
Covid-19 infected lung detection using machine learning
(Brac University, 2021-01)In every 100 years, there has been a pandemic all around the world. The globe faced Plague, Cholera, and Spanish Flu in the years 1720, 1820, and 1920, respectively. Coronavirus, commonly known as Covid-19, is currently ... -
Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning
(Brac University, 2021-01)Retinal disease diagnosis by machine learning can be achieved using Deep Neural Network based predictors. Use of Explainable Artificial Intelligence (XAI) has the potential to explain the black box of those neural network ... -
A deep learning approach for pneumonia classification from chest X-Ray images with ensemble modelling and explainable AI
(Brac University, 2021-06-08)Pneumonia is one of those frightening diseases that has a high mortality rate among children and the elderly, with an estimated 2 million fatalities per year. Pneumonia affects the poorest people in Africa and Asia the most, ... -
A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
(Brac University, 2021-10)Depression and mental health issues (stress, nervousness, panic attacks, anxiety attacks etc.) are nowadays a major issue in the whole world. It is a common cause of mental illness that has been linked to an increased ... -
Detecting brain tumor using deep neural networks from MRI images
(Brac University, 2021-06)A brain tumor is a collection of abnormal cells growth in brain. It is a neurological disease which causes great damage and affects other healthy cells of brain. It can be cancerous or non-cancerous. Nowadays, people are ... -
Detection of intracranial hemorrhage on CT scan images using convolutional neural network
(Brac University, 2021-09)Intracranial hemorrhage is an acute bleeding within the skull which can damage the brain tissue and can eventually lead to disability or even death. It is a serious medical condition that occurs when blood is built up ... -
Detection of Parkinson’s disease from Neuro-imagery using deep neural network with transfer learning
(Brac University, 2020-04)Parkinson’s disease is a neurological condition that is dynamic and steadily influences the movement of the human body. It causes issues within the brain and slowly increments time by time. Tremor is the major side effect ... -
An efficient approach for recyclable waste detection and classification using image processing techniques
(Brac University, 2023-01)One of the world’s most pressing issues right now is the lack of a competent waste management system, particularly in emerging and underdeveloped countries. Re cycling solid waste, which comprises numerous dangerous ... -
An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
(Brac University, 2022-05)Optical Coherence Tomography (OCT) is an effective approach for diagnosing retinal problems that can be used in combination with traditional diagnostic testing methods. We developed and implemented a deep Convolutional ... -
An efficient face recognition model using multiple angular images and deep neural network architecture
(Brac University, 2023-01)Face surface information in three dimensions is one of the promising biometric modality that can improve the identification and increase the accuracy of verification of face recognition systems in challenging situations.This ... -
Eve-teasing detection from video footage using computer vision and artificial intelligence
(Brac University, 2023-01)We present computer vision approaches combined with machine learning techniques to detect eve-teasing from any video material, which may be used in any situa tion. Eve teasing is a colloquial term for public sexual ... -
Homomorphic encryption on deep learning in accurate prediction of brain tumour
(Brac University, 2023-01)The brain is the most complicated organ that manages every bodily function as well including intellect, memory, emotion, taste, motor skills, vision, respiration, temperature, and appetite. Any type of disease or damage ... -
Identifying brain abnormalities using image processing and CNN models
(Brac University, 2021-06)In a developing country like Bangladesh, it is tough to detect a brain abnormality, i.e., Pituitary tumor, Glioma, Meningioma, etc., in an early stage and treat them accordingly. In our proposed system, ML(Machine Learning) ... -
Interpretable COVID-19 classification leveraging ensemble neural network and explainable AI
(Brac University, 2021-06)COVID-19 which is also none as Corona Virus Disease is rst discovered in a city of China named Wuhan at December 2019 and it has been announced as a global pandemic at the middle of 2020. SARS-CoV-2 virus COVID-19 and ...