Now showing items 1-20 of 86

    • Accurate analysis of mood detection using eye-images rather than facial expression recognition (FER) 

      Hossain, Arafat; Chakraborty, Akash; Syara, Syeda Rifa; Rahman, Saadman; Tanmoy, Fahad Muntasir (Brac University, 2022-06-05)
      There are several works on mood detection by machine learning from physical and neuro- physical data of people, along with works on emotion recognition using eye-tracking. We want to show that a person’s mood can be detected ...
    • An advanced hospital rating system using machine learning and natural language processing 

      Tamjid, Ali Asgar; Galpo, Gaurab Paul; Urmi, Khadija Begum; Chitto, Fatema Sadeque; Annafi, Sadia (Brac University, 2023-05)
      Bangladesh is the host of 255 public and 4,452 private hospitals. Unfortunately, there is no reliable metric or resource available online to determine which hospital is better. Patients and their peers often find it ...
    • Analysis of financial data on the time series using data from the stock market 

      Shachcha, Ifad Bhuiyan; Siam, Muhammad Ziaus (Brac University, 2022-05)
      Predicting financial data is really important for investors Often times investors do not have a proper tool to properly assess the market and forecast their predictions. Furthermore, not only investors in modern day ...
    • Analyzing the security of e-Health data based on a hybrid federated learning model 

      Shafin, Md. Mehtabul Islam; Akhter, Sabrin; Hasan, Mohammad Shafkat; Nasimuzzaman, Md.; Prithul, Tamzeedur Rahman (Brac University, 2023-01)
      This research aims to provide an approach for analyzing the security of the e-health care system through the use of federated learning and the pre-processing of distinct deep learning models. The infrastructure for ...
    • Application of machine learning in attentiveness detection from EEG signal 

      Ridi, Sadia Sobhana; Tandra, Jannatul Farzana; Emon, Mahmudul Hasan; Mahmud, Md Ridwan; Tabassum, Sumaiya (Brac University, 2022-09-29)
      Brain-computer interface (BCI) spellers enable severely motor-impaired people to communicate through brain activity without the use of their muscles. Our brains precisely predict what we will think. If a human-readable ...
    • Automated image caption generator in Bangla using multimodal learning 

      Rodoshi, Mashiat Hasin; Ahmed, Moin Uddin; Ashraf, Md. Sobhan; Mim, Md. Galib Hasan; Khanam, Ashfia (Brac University, 2023-01)
      Experiencing an image on-screen is a privilege that we often seem not to care about. A visually impaired person does not have that luxury. A system that can automatically produce closed captions of an image can thus help ...
    • Automatic brain tumor segmentation using U-ResUNet chain model approach 

      Alam, Mohd Tanjeem; Nawal, Nafisa; Nishi, Nusrat Jahan; Sahan, MD Samiul; Islam, Mohammad Tanjil (Brac University, 2021-09)
      Identifying brain tumors precisely within the early stage is still a challenging problem for the medical sector consistent with recent research. In a previous research approved by Cancer. Net Editorial Board, it was ...
    • Bangali Handwritten characters classification using Deep Convolutional Neural Network 

      Sikder, Shihab Uddin; Muslebeen, Md. Shafiul (Brac University, 2022-05)
      Handwritten letter classification of any given language has the potential to be used in various fields such as literature, educational institutions, digitization of govern ment records etc. Bengali language with its complex ...
    • Bengali hand sign language recognition using convolutional neural networks 

      Rumi, Roisul Islam; Hossain, Syed Moazzim; Shahriar, Ahmed; Islam, Ekhwan (BRAC University, 2019-04)
      Throughout the world the number of deaf and mute population is rising ever so increasingly. In particular Bangladesh has around 2.6 million individuals who aren't able to communicate with society using spoken language. ...
    • Biometric retina identification using artificial approach 

      Imam, Syed Abrar; Huda, Sheikh Samiul; Alam, Talha Bin; Ahsan, Anika (Brac University, 2022-05)
      In this paper, we considered recognizing 2D retina pictures with a Convolutional Neural Network (CNN) for greater accuracy since retina-based identification is the most secure way of establishing identity and identifying ...
    • Blockchain-based traffic surveillance footage authenticity detection system 

      Bin Moshiur, Tasnimul; Ullah, Mohammad Zafar; Nawar, Nahian; Tazwar, Tawsif Muhammed; Nanjiba, Rifah (Brac University, 2023-01)
      With the advancement in technology, fraudulent videos are becoming harder to de tect and easier to produce. Surveillance footage can serve as circumstantial evidence when dealing with crimes, however when this footage is ...
    • Cancer classification using deep learning from medical image data 

      Monir, Raiyan Janik; Shaon, Shoeb Islam; Noman, Syed Mohammad; Iqbal, Sahariar (Brac University, 2022-01)
      Cancer is a disease in which some of the body’s cells grow uncontrollably and spread to other parts of the body. Cancer can start almost anywhere in the human body, which is made up of trillions of cells. There is usually ...
    • Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN 

      Bhuiyan, Mazedul Haque; Tabassum, Fariba; Bushra, Umme; Shwon, Md.Mahbub Rahman (Brac University, 2020-04)
      Uterine cervical cancer is the second most regular gynecological harm around the world. The appraisal of the degree of sickness is fundamental for arranging ideal treatment. Imaging procedures are progressively utilized ...
    • Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children 

      Alhossen, Md.; Himi, Rafika Zannat; Hasan, Zahid (Brac University, 2021-05)
      The world is changing with the pace of information technology revolution and now a-days anybody can access to the internet including the children. Since birth These 21st century children are able to access to the di erent ...
    • 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 ...
    • Classification of Bangladeshi soil texture using convolutional neural network 

      Raj, Hafiz Mohiuddin; Shahreen, Sazia; Shah, Muntaha Binte; Evan, Syed Washinur Ashraf; Abdullah, Juhayer (Brac University, 2022-09-29)
      In agriculture, soil is one of the most potential output sources. That is why, if we can foresee the soil’s nature and how it will turn in the future as well as it’s other qualities, we may achieve adequate monitoring ...
    • Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques 

      Ahasan, Md. Mubtasim; Fahim, Mohammad; Mazumder, Himadri; Fatema, Nur E; Rahman, Sheikh Mustafizur (Brac University, 2022-01)
      Infectious and non-infectious respiratory diseases are among the major reasons for deaths, financial and social crises around the world. However, medical personnel still find it very difficult to detect the diseases using ...
    • Classification of damaged vegetation areas using convolutional neural network over satellite images 

      Haque, Samiha; Rahman, Nazibur (Brac University, 2021-01)
      Forests and wild vegetation have always been highly significant natural resources throughout history and play a crucial role in keeping the climate and ecosystems well balanced. Over the years, there has been a growing ...
    • A color vision approach considering weather conditions based on auto encoder techniques using deep neural networks 

      Raj, Mohammad Mainuddin; Tasdid, Samaul Haque; Nidra, Maliha Ahmed; Noor, Jobaer; Ria, Sanjana Amin (Brac University, 2021-01)
      Color vision approach is a riveting field of technology crucial in pioneering innovations like autonomous vehicles, autonomous drone deliveries, automated stores, robots, infrastructure and surveillance monitoring programs ...
    • A comparative study of deep learning methods for automating road condition characterization 

      Ruhi, Zurana Mehrin; Sheetal, Farahatul Aziz; Prithu, Farisha Hossain (Brac University, 2020-04)
      Roads in Bangladesh provide infrastructural facilities to both agricultural as well as industrial sectors of the country. Distressed roads can cause fatal accidents as well as largely decelerate sector progress. This makes ...