Now showing items 1-20 of 47

    • Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks 

      Awwal, Alvina; Shomee, Homaira Huda; Sadat, Sayed Us; Amin, Sadia Nur (Brac University, 2021-01)
      Alzheimer’s disease (AD) is a neurological disease that affects the healthy cells of the brain and results in people having long-term memory loss, thinking problems, disorientation, behavioral inconsistencies and finally ...
    • Applying tDCS over the dominant Hemisphere to observe event-related Desynchronization 

      Khan, Akif Ahmed; Bastob, Abu Wakkas; Ahmed, Bushra; Reza, Abdullah Al (Brac University, 2019-12)
      Although keeping us alive is arguably the most important function of the human brain, the human brain is responsible for a host of functions|including processing of environmental stimuli. Electroencephalography (EEG) is ...
    • Classi fication of motor imagery tasks based on BCI paradigm 

      Hossain, Nahid; Hasan, Bhuiyan Itmam; Mohona, Mahfuza Humayra; Noshin, Kantat Rehnuma (Brac University, 2019-09)
      Motor imagery tasks are mental processes by which individual practices a set of actions in their mind without actually performing the physical movements. Research in the motor imagery tasks allow us to acquire critical ...
    • Cognitive load detection of vision impaired in the inward places using Bio-signal 

      Kabir, Raiyan; Rashid, Md. Mamun Or (Brac University, 2019-12)
      In this current world, approximately 290 millions of people are partially or fully blind. They can not roam around like the normal people. Visually Impaired People (VIP) have to face many obstacles everyday in inward and ...
    • A comparative analysis of emotion recognition using EEG signals with a channel selection technique 

      Riduan, Jonayed Ahmed; Mahjabin, Most.; Mim, Nadia Tasnim; Islam, Ridwane-ul; Rana, Md. Shahriar Rahman (Brac University, 2021-01)
      Emotion can be defined as the neurophysiological changes people experience due to significant internal or external occasions. This is a mental condition that can a↵ect a person’s behavior, mood, way of life, and relationship ...
    • Comparative study of X-ray and CT scan images for the detection of COVID-19 using deep learning 

      Niloy, Ahashan Habib; Shiba, Shammi Akhter; Fahim, S.M. Farah Al; Faria, Faizun Nahar; Rahman, Md. Jamilur (Brac University, 2015-08)
      Coronavirus 2019 (in short, COVID-19), originated in the Wuhan province of China in December 2019, has been declared a global pandemic by WHO in March 2020. Since its inception, it’s rapid spread among nations had initially ...
    • Comparison of different CNN architectures for brain tumor detection using fMRI 

      Mashiat, Afsara; Akhlaque, Reza Rifat; Fariha, Fahmeda Hasan; Patwary, Md Shawkat Hossain (Brac University, 2020-04)
      Brain is the most vital organ of human body which controls the entire nervous system of human body. In that case, if anything goes wrong inside our brain the entire nervous system gets collapsed. The brain tumors are the ...
    • Consumer behaviour analysis using EEG signals for Neuromarketing Application 

      Amin, Chowdhury Rabith; Hasin, Mirza Farhan; Leon, Tasin Shafi; Aurko, Abrar Bareque (Brac University, 2019-12)
      Neuromarketing is applying neuropsychology in marketing research which studies consumer sensory-motor such as cognitive and affective response to marketing stimuli with the help of modern technologies. It is one of the ...
    • Conversion of Bengali speech to text using long short-term memory(LSTM) 

      Chowdhury, Mohammad Fahim; Sultana, Zakia; Jahan, Nusrat; Alavi, Safkat Hasin (Brac University, 2021-01)
      Speech to text conversion is a remarkable topic in the field of Artificial Intelligence which is undoubtedly a significant medium of expressing human feelings and thoughts. However, if we compare it with text to speech, ...
    • COVID-19 related fake news detection model 

      Shondhy, Sumaiya Islam; Khan, Forhad Ahmed; Ibrahim, Syed Shoaib; Barua, Shuvajit (Brac University, 2021-01)
      In this era of developed information and technology, any sort of information runs faster than air. The reliability of the information can be tricky at times. Some news publishing sources can publish news that are actually ...
    • Design and evaluation of convolutional neural network for detection of Alzheimer’s disease using MRI data 

      Mahbub, Riasat; Azim, Muhammad Anwarul; Reza, Khondaker Masfiq; Mahee, Md Nafiz Ishtiaque; MD. Zahidul Islam Sanjid (Brac University, 2021-09)
      Alzheimer’s Disease (AD) is a neurological condition where the decline of brain cells causes acute memory loss and severe loss in cognitive functionalities. Various Neuroimaging techniques have been developed to diagnose ...
    • Detecting Deepfake images using deep convolutional neural network 

      Dhar, Arpita; Acharjee, Prima; Biswas, Likhan; Ahmed, Shemonti; Sultana, Abida (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 ...
    • Detecting navigation challenges for the visually impaired with mobile monitoring of biosignal 

      Islam, Mohammad Waseq ul; Tasnim, Ridwana; Bhuiyan, MD. Hasib Ullah (Brac University, 2020-04)
      In recent years, mobile Brain Computer Interface (BCI) has gained much popularity in the design of navigation aids. This opens up the platform to build navigation aids based on the level of stress imposed on visually ...
    • Detection of alzheimer's disease using deep learning 

      Hasan, Mahmudul; Hassan, Syed Zafrul; Azmi, Tanzina Hassan; Hossain, Emtiaz (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 amyotrophic lateral sclerosis using signal processing and machine learning 

      Ali, Zohair Mehtab (Brac University, 2019-04)
      Electromyography(EMG) signals provide signi cant information for the diagnosis of neuromuscular disorders like Amyotrophic Lateral Sclerosis(ALS) which is a form of Motor Neuron Disease(MND). Due to the stochastic nature ...
    • Detection of early stages of Parkinson's disease by analyzing fMRI data and machine learning approaches 

      Neehal, Ahmed Hasin; Azam, Md. Nura; Islam, Md. Sazzadul; Hossain, Md. Ishrak (Brac University, 2019-12)
      Parkinson's Disease is a progressive nervous system brain disorder which affects motor neuron loss control and movement coordination. Parkinson's symptoms are shown gradually and get worse over time. Its signs and symptoms ...
    • Detection of epileptic seizure using Support Vector Machine Classifier - extracted features from EEG signals 

      Amiz, Asef Hassan; Talukder, Md. Golam Muid; Shahriar, Labib; Chowdhury, Sahal Ahamad; Hasan, Md. Mehedi (Brac University, 2021-06)
      Epilepsy is the most common neurological issue in people after stroke. Around 40 or 50 million individuals on the planet endure epilepsy. Epilepsy is characterized by an irregular seizure in which abnormal electrical ...
    • Detection of intracranial hemorrhage on CT scan images using convolutional neural network 

      Rahman, Afridi Ibn; Bhuiyan, Subhi; Reza, Ziad Hasan; Zaheen, Jasarat; Khan, Tasin Al Nahian (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 mind wandering using EEG signals 

      Tasika, Nadia Jebin; Alam, Salwa; Rimo, Mohsena Begum; Haque, Mohtasim Al; Haque, Mohammad Hasibul (Brac University, 2020-01)
      Mind Wandering (MW) is the recurrent occurrence in which our mind gets disengaged from the immediate task and focused on internal trains of thought. In terms of intelligent interfaces MW can both have good as well as ...
    • Detection of Parkinson’s disease from Neuro-imagery using deep neural network with transfer learning 

      Asaduzzaman; Sakib, A.F.M. Nazmus; Shusmita, Sanjida Ali; Kabir, S. M. Ashraf (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 ...