Now showing items 517-536 of 1465

    • E-learning software in the context of Bangladesh : proposal for an interactive model according to bloom's texonomy 

      Raihan, Ariful Hoque; Shahriyar, Sheikh Sadik (BRAC University, 2007)
      The latest information and communication technologies like internet service, telecom service, and live video conference have introduced a special form of distance learning: e-learning which removes the barriers of traditional ...
    • EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence 

      Mim, Ankhi Akter; Ashakin, Kazi Habibul; Hossain, Sadat; Orchi, Nabiha Tasnim; Him, Al Shahriar (Brac University, 2024-01)
      Advances between medical imaging and artificial intelligence (AI) have led to improvements in cancer diagnosis and classification. This paper provides a new framework called Explainable AI for cancer categorization ...
    • Early detection of breast cancer using machine learning 

      Fuad, Wasi Mohammad (Brac University, 2018-12)
      Breast cancer is the most common cancer among women but in can occur in both the genders. It is accountable for an appalling number of deaths worldwide. In a particularly low-resource developing country like Bangladesh, ...
    • Early detection of cervical cancer using deep neural networks 

      Akhund, Atoshi; Ahmad, Saad; Taki, Sarwar Siddiqui (Brac University, 2022-05)
      Cervical cancer is a disease that is mostly preventable, but it is one of the major causes of cancer fatality in women worldwide. Several studies say that annually 2,60,000 women die because of cervical cancer. Chronic ...
    • Early detection of chronic kidney disease using machine learning 

      Abrar, Tahmid; Tasnim, Samiha; Hossain, Md. Mehrab (Brac University, 2019-09)
      Chronic kidney disease (CKD) is a global prevalent ailment that causes lives in a predominant number. CKD is the 11th most deadly cause of global mortality with 1.2 million death each year and according to kidney Foundation ...
    • Early detection of diabetic retinopathy using deep learning techniques 

      Gomes, Veronica Jessica; Alavee, Kazi Ahnaf; Sarda, Anirudh; Akhand, Zebel-E-Noor (Brac University, 2021-10)
      We, humans, are the bearer of diseases. While most of them have a thoroughly researched and contemplated solution set, some of them do not. Diabetes is one of those common diseases that do not have a clear solution but ...
    • Early detection of parkinson’s disease using image processing and artificial neural network 

      Rumman, Mosarrat; Tasneem, Abu Nayeem; Farzana, Sadia (BRAC University, 2018-04)
      Early detection of Parkinson‟s Disease (PD) is very crucial for effective management and treatment of the disease. Dopaminergic images such as Single Photon Emission Tomography (SPECT) using 123I-Ioflupane can substantially ...
    • Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique 

      Shakir, Mohsinul Bari; Hossain, Mohammad Amzad; Shams, Khan Mohammad Aymaan; Akib, Faisal Raihan (BRAC University, 2017)
      Advancements in computing speed and power have made revolutionary changes in medical science practices and this is no different for cardiology. Such advancements in computer sciences have made the existing medical tests ...
    • Early fire detection using enhanced optical flow analysis technique 

      Khondaker, Arnisha; Khandaker, Arman (BRAC University, 2018-04)
      This paper proposes a multi-stage fire detection model that consists of chromatic segmentation, shape analysis and differential optical flow estimation. At the initial phase, color segmentation is carried out which takes ...
    • Early grade prediction using profile data 

      Iqbal, Sumaiya; Muntaha, Mahjabin; Natasha, Jerin Ishrat; Sakib, Dewan (Brac University, 2020-04)
      Universities are reputable institutions for higher education and therefore it is crucial that the students have satisfactory grades. Quite often it is seen that during the first few semesters many students dropout from ...
    • Early prediction of Alzheimer's disease using convolutional neural network 

      Abed, Mahjabeen Tamanna; Nabil, Shanewas Ahmed; Fatema, Umme (Brac University, 2019-08)
      Neuroimaging can be a prospective instrument for the diagnosis of Mild Cognitive Impairment (MCI) along with its more severe stage, Alzheimer's disease (AD). High- dimensional classi cation methods have been commonly ...
    • Early Schizophrenia Diagnosis with 3D Convolutional Neural Network 

      Ashraf, S.M. Nabil; Oikko, Isbat Mashiat; Saha, Chayan; Anik, Md. Rakib Enam (Brac University, 2021-06)
      The proper prediction of schizophrenia at an early stage can be very beneficial to those who are at risk of developing it at a severe stage later on. The early signs of schizophrenia include extreme reaction to criticism, ...
    • Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images 

      Hossain, Mainul; Haque, Shataddru Shyan; Ahmed, Humayun; Mahdi, Hossain Al; Aich, Ankan (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 ...
    • Early threat warning via speech and emotion recognition from voice calls 

      Ishtiak, Ifaz; Rahman, Mohammad Mazedur; Usmani, Md.Razaul Haque (BRAC University, 2018-12)
      The aim of this system is to identify potential cases of threats, and provide an early warning or alert to such cases. This will be based on voice such as voice chat over telecommunication networks or social media. The ...
    • ECG disease detection & feature extraction by wavelet transformation 

      Imam, Saif; Tabassum, Tasbiha; ZarinIrtiza (BRAC University, 2016-03)
      ECG is the most common and basic test to run on patients to check any kind of anomalies in the heart. In the ECG result 10 to 20 minutes long continuous data of a patient’s heart is down sampled and printed as a 1D graph. ...
    • Ecommerce Web Application 

      Pantha, Khaled Mahmud (Brac University, 2022-09)
      ECommerce is the term used to describe the selling of products and services online. It’s one of the most dynamic industries in the world, and it’s growing faster than ever in the past few years. In 2016, ecommerce sales ...
    • Economic crisis prediction due to pandemic outbreak using machine learning 

      Ahmed, Tanvir; Hasan, MD. Nahid; Ashik, Md.; Hasan, Md. Jahid (Brac University, 2021-06)
      Since pandemic disease outbreaks are causing a major financial crisis by affecting the worldwide economy of a nation, machine learning techniques are urgently required to forecast and analyze the economy for early economic ...
    • Economic crisis prediction due to pandemic outbreak using machine learning 

      Ahmed, Tanvir; Hasan, MD. Nahid; Ashik, Md.; Hasan, Md. Jahid (Brac University, 2021-01)
      Since pandemic disease outbreaks are causing a major financial crisis by affecting the worldwide economy of a nation, machine learning techniques are urgently required to forecast and analyze the economy for early economic ...
    • Edge detection for mobile robots in Lunar Surface and surroundings 

      Iqbal, Mehtab (BRAC University, 2012-04)
      The goal of this paper is to explore possibilities in devising a system that is able to detect obstacles in a scene or situation where color variation is limited and environment is noisy, such as that of the moon where ...
    • Edge-optimized machine learning models for real-time personalized health monitoring on wearables 

      Rafee, Athar Noor Mohammad; Dutta, Antu; Haque, Afsan; Rahman, Asif; Barua, Aditta (Brac University, 2024-01)
      Personalized health monitoring, including Human Activity Recognition (HAR) and Fall Detection, is crucial for healthcare. Traditionally, most research in this field has relied on wearable sensors to collect data. The ...