Browsing by Subject "Deep learning"
Now showing items 41-60 of 122
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DeepWPD: A deep learning based wavelet packet decomposition to remove Moiré pattern from screen capture images.
(Brac University, 2022-09)Moiré artifacts is a special type of noise which is rarely considered in deep learning based image processing tasks. But with the increasing number of digital screens like TV, laptop, desktop screens etc. it is becoming ... -
Demand forecasting on supply chain using ML and NN
(Brac University, 2022-05)Demand forecasting is mainly a process whereby analyzing historical sales data, strategic and operational strategies are devised in order to estimate customer demand. One of the most fundamental aspects of supply chain ... -
Demystifying black-box learning models of rumor detection from social media posts
(BRAC University, 2021-09)Social media and its users are vulnerable to the spread of rumors, therefore, protect ing users from these rumors spread is extremely important. This research proposes a novel approach for rumor detection in social media ... -
Density based traffic control system for a four way intersection
(Brac University, 2023-01)Intelligent traffic system is not new to this modern world in order to mitigate traffic congestion. However, a proper management plan for a four way intersection lacks in our cities. An enhanced and optimized system is ... -
Detecting Deepfake images using deep convolutional neural network
(Brac University, 2021-09)In recent years, advancement in the realm of machine learning has introduced a feature known as Deepfake pictures, which allows users to substitute a genuine face with a fake one that seems real. As a result, distinguishing ... -
Detection and 3D visualization of Brain tumor using deep learning and polynomial interpolation
(Brac University, 2019-04)Among di erent imaging techniques MRI, MRSI and CT scans are some of the widely use techniques to visualize brain structures to point out brain anomalies especially brain tumor. Identi cation of brain tumor accurately ... -
Detection of alzheimer's disease using deep learning
(Brac University, 2019-12)Machine Learning has been on top of its form over the last few years. It covers a vast area of predictive web browsing, email and text classification, object detection, face recognition etc. Among all of the other ... -
Detection of coronary artery blockage at an early stage using effective deep learning technique
(Brac University, 2022-09-28)A coronary artery blockage is a form of coronary artery disease also known as CAD. It is the most common and frequent disease affecting the human body over the age of 65. CAD is a type of cardiovascular disease that ... -
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 ... -
Dynamic image analysis for abnormal behavior detection
(BRAC University, 4/18/2017)Our world is now in such developing state where security is more of a concern rather than privacy for an individual. Nowadays, abnormal behavior detection system plays a very important role in various sectors such as, ... -
Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images
(Brac University, 2022-01)Colon cancer is one the most prominent and daunting life threatening illnesses in the world. Histopathological diagnosis is one of the most important factors in determining cancer type. The current study aims to create ... -
An efficient approach for binary classification in brain tumor detection using convolutional neural network
(Brac University, 2022-01)Brain tumor detection using Convolutional Neural Network (CNN) models with binary classification has significantly improved the reliability of medical imaging through Deep Learning. The purpose of this research is to ... -
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 for detecting Alzheimer’s disease using brain images
(Brac University, 2022-01)Alzheimer’s disease (AD) is a disorder of the brain which causes the loss of memory. This is a successively growing disease which means the severity of it will be upward with the time. In this century, AD is one of the ... -
An efficient deep learning approach to detect neurodegenerative diseases using retinal images
(Brac University, 2023-01)Neurodegenerative disorders are diagnosed through undergoing brain MRI, CT scans, genetic testing, and various laboratory screening tests which are often tedious, time consuming and beyond the means of most people’s financial ... -
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 deep learning approach to detect skin Cancer
(Brac University, 2021-09)Each year, millions of people around the world are affected by cancer. Research shows that the early and accurate diagnosis of cancerous growths can have a major effect on improving mortality rates from cancer. As human ... -
Ejection fraction estimation using deep semantic segmentation neural network on 2D Echocardiography data
(Brac University, 2020-04)Ejection fraction value denotes how much blood is pumped out of the heart to different parts of the body. It is a routine clinical procedure in heart function assessment, where the left ventricle of the heart has to be ... -
Electroencephalogram based Emotion Recognition with Graph Convolutional Network Model
(Brac University, 2022-09)Recently, researchers have focused on understanding human sentiment using mechanical devices or reactions to any machinery activity. Computerization is becoming more prevalent in today’s environment. People are unaware of ...