Browsing by Subject "InceptionV3"
Now showing items 1-12 of 12
-
Analyzing students’ concentration in online courses through Webcam
(Brac University, 2024-01)Online learning is growing in popularity these days. As a result, students typically contribute millions of course-related responses to discussion forums and exchange some learning experiences. This study focuses on ... -
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 ... -
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 ... -
A comparative study of lung cancer prediction using deep learning
(Brac University, 2022-09)At the point when cells in the body develop out of control, this is alluded to as cancerous development. Lung cancer is the term used to depict cancer that starts in the lungs. At first in the field, classifier-based ... -
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 ... -
Diabetic retinopathy detection and classification by using deep learning
(Brac University, 2022-01)Eyes are the most sensitive part of a human being and it is one of the most challenging tasks for a computer-aided system to classify its diseases. Many visionthreatening diseases such as, Glaucoma and Diabetic Retinopathy ... -
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 ... -
Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
(Brac University, 2022-09)Chronic kidney disease, often called chronic kidney failure, is a steady decline of renal function. Some of the most common reasons for kidney failure are cyst, stone and tumor. There may be no symptoms of chronic renal ... -
Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
(Brac University, 2022-01)Due to our unhealthy diets and the consumption of enhanced cholesterol in our daily lives, our health has become vulnerable and at risk of different types of cardiac diseases. The most common of them is Myocardial ... -
Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
(Brac University, 2020-06)Transfer learning techniques in deep learning is nowadays a raising and promising field of research and a tool for Artificial Intelligence with a lot of prospects. Our goal is to predict Glaucoma from fundus images to help ... -
Skin disease detection and classification using deep learning
(Brac University, 2022-01)Skin Diseases have been the primary focus of this study, as they are one of the most lethal diseases if not diagnosed and treated early. The research will enable the fields of Medical Science and Computer Science to ... -
Two dimensional convolutional neural network CNN approach for detection of Bangla sign language
(Brac University, 2022-09-28)Sign language is known as the primary communication medium for deaf and mute people. But the lack of available resources and a steep learning curve deter the average person from learning it making communication with the ...
