Now showing items 21-40 of 52

    • An efficient deep learning approach for detecting Alzheimer’s disease using brain images 

      Sani, Mehedi Hasan; Rahman, Mohibur; Achib, Md. Abdullah Al; Hossain, Rakib (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 Brain Tumor using MRI images 

      Islam, Annur Tasnim; Apu, Sakib Mashra; Sarker, Sudipta; Hasan, Inzamam M.; Shuvo, Syeed Alam (Brac University, 2021-10)
      A brain tumor is the development of mutated cells in the human brain. Many di er- ent types of brain tumors exist nowadays. According to researchers and physicians, some brain tumors are non-cancerous while some are ...
    • An efficient deep learning approach to detect COVID-19 infected lungs using image data 

      Kabir, Asif Rezwan; Roy, Shutirtha; Zerin, Nusrat; Afrin, Sheikh Sharia; Choudhury, Anika Jahan (Brac University, 2022-01)
      The beginning of 2020 will always be a dreadful chapter in human history. Even with all the recent advancements in the medical sector, the COVID-19 virus proved to be a major challenge for doctors all over the world. The ...
    • An efficient deep learning approach to detect retinal disease using optical coherence tomographic images 

      Khan, Farhan Sakib; Ferdaus, Nowshin; Hossain, Tamim; Islam, Quazi Sabrina; Islam, Md. Iftakharul (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 

      Islam, Ashfaqul; Khan, Daiyan; Chowdhury, Rakeen Ashraf (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 ...
    • Efficient image processing and machine learning approach for predicting retinal diseases 

      Hasib, Mehadi Hasan; Sultana, Tasnim; Chowdhury, Chandrika (Brac University, 2020-04)
      As the computational technology and hadrware system improved over time, the use of neural network in image processing has become more and more prominent. Soon deep learning also caught the attention of the medical sector ...
    • An efficient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling 

      Sagor, Mostofa Kamal; Jahan, Ishrat; Chowdhury, Susmita; Ansary, Rubayet (Brac University, 2021-01)
      Among the most convenient bacteriological assessments for the diagnosis and treatment with several health complications is the chest X-Ray. The World Health Organization (WHO) estimates, for instance, that pneumonic plague ...
    • Faster image compression (LZW algorithm) technique using GPU parallel processing 

      Soobhee, Ateeq-Ur-Rahman; Ruma, Kamrun Nahar; Ahsan, Md. Fakhrul; Hossain, F. M. Fahmid (BRAC University, 12/26/2017)
      Since the beginning till present, the technology demands to store as massive data as possible in as little space as possible. As web, mobile, desktop and all other applications use image for different purposes, image ...
    • Generation of realistic images from human drawn sketches using deep learning 

      Mahbub, Mohammed Julfikar Ali; Rahmatullah, S. Afsan; Rahman, G M Sohanur; Zillanee, Abu Hasnayen; Akib, Aknur Kamal (Brac University, 2022-01)
      Processing sketches to produce realistic images is an intriguing idea in the world of emerging Artificial Intelligence. We present a Generative Adversarial Network (GAN) based methodology that creates satisfactory images ...
    • Handwritten Bangla character recognition to braille pattern conversion using image processing and machine learning 

      Abir, Tawhidur Rahman; Ahmed, Touseef Saleh Bin; Rahman, Md. Tausif; Jafreen, Sumaiya (BRAC University, 2018-12)
      There has been significant development in the recent Education System with the rapid development of technology however there are very few facilities that can help those people with disabilities such people without sight. ...
    • Integration of handcrafted and deep neural features for Melanoma classification 

      Rahman, Mohammad Saminoor; Hossain, Md. Jubayer; Islam, Siful; Kabir, Md. Nafiul; Sujon, Md. Kamrul Hasan (Brac University, 2021-09)
      Deep neural networks (DNNs) are widely utilized to automate medical image in- terpretation in many forms of cancer diagnosis and to support medical specialists with fast data processing. Although man-made characteristics ...
    • Interpretable COVID-19 classification leveraging ensemble neural network and explainable AI 

      Dipto, Shakib Mahmud; Afifa, Irfana; Kabir, Sumya (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 ...
    • Investigation assistant with suspect anticipating intelligence 

      Abdullah, Saqueeb; Nibir, Farah Idid; Salam, Suraiya; Dey, Akash (Brac University, 2019-08)
      Truly settling crimes have been the privilege of the criminal justice and law enforcement specialists. With the expansion of the utilization of the computerized system to track violations and follow culprits, computer ...
    • Iris communicator 

      Ali, Shahriar; Arnob, Nafis Hasrat (BRAC University, 2018-12)
      This research purposes an eye pupil tracking experimental software to enable communication abilities for individuals with severe motor impairment. Since the ability of moving eye pupil is often preserved, even in severe ...
    • Learning a deep neural network for predicting phishing website 

      Das, Robat; Hossain, Md. Mukhter; Islam, Shariful; Siddiki, Abujarr (Brac University, 2019-05)
      In recent years, we have seen a huge paradigm shift in business because of the fast development of the Web. For this reason, consumers change their tendency from customary shopping to the electronic business. In the time ...
    • Lossless segmentation of Brain Tumors from MRI images using 3D U-Net 

      Farha, Ramisa; Nuha, Nigar Sultana; Sakib, Syed Nazmus; Rafi, Sowat Hossain; Khan, Md Sabbir (Brac University, 2022-01)
      2D computer vision and activities related to medical image analysis are remarkably guided with the help of Convolutional Neural networks (CNNs) in recent years. Since a chief portion in the available clinical imaging ...
    • Machine learning approach for improving decision support in ICU 

      Siddiquee, Mohib Billah; Fuad, Mostofa Jamil; Azmain, Md. Fahim (BRAC University, 2018-07)
      Patients in the intensive care unit (ICU) receive a deep observation for controlling and responding to their rapidly changing physiological conditions. The quality of their care depends on clinical staff combining large ...
    • A machine learning approach to analyze and predict rainfall in different regions of Bangladesh 

      Rahee, Arnob; Nafiz, Md. Montasir; Bhuiyan, Sania Azhmee (Brac University, 2021-08)
      Rainfall has always been important in context of Bangladesh as almost 43% of the population depends on agriculture for their livelihood. Global warming has been taking a toll on environment and rainfall patterns have ...
    • A machine learning approach to detect depression and anxiety using supervised learning 

      Ullas, Md Tahmidur Rahman; Begom, Mariyam; Ahmed, Anamika; Sultana, Raihan (BRAC University, 2019-04)
      Depression, a major depressive disorder and anxiety are common medical illness which cause several symptoms that a ect the way a person feels, thinks, and the way he/she acts. These disorders are not only hard to endure, ...
    • Multi-modal emotion recognition for determining employee satisfaction 

      Hussain, Saadat; Zaman, Farhan Uz; Zaman, Maisha Tasnia; Kabir, Nahian (Brac University, 2020-04)
      Emotion Detection has been very popular in the field of research for a couple of years. In the past, emotion recognition has been studied and applied in order to detect the overall emotional state of a person using ...