Now showing items 1-20 of 24

    • 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 ...
    • Cassava leaf disease classification using deep learning and convolutional neural network ensemble 

      Shahriar, Hasan; Shuvo, Protick Sarker; Fahim, Md. Saidul Haque; Sordar, Md Sobuj; Haque, Md Esadul (Brac University, 2022-01)
      Cassava is a high-protein and nutrient-dense plant, notably inside the leaves. Cassava is often used as a rice alternative. Pests, viruses, bacteria, and fungus may cause a variety of illnesses on cassava leaves. This ...
    • 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 ...
    • Comparative data analysis of a PV module system considering weather parameters 

      Ahmed, Nafiz; Hoque, Khandoker Samiul; Ahmad, Sabbir; Siddiki, Didar Alam (Brac University, 2021-06)
      Fastest growing economy of Bangladesh increase the great demand of power generation using renewable energy sources. However, uncertainty in the output power of the photovoltaic (PV) power generation station due to variation ...
    • Cosmic super string detection using dilated convolutional neural network with focal loss 

      Ishrak, Mohammed Hasin (BRAC University, 2018)
      Cosmic string are objects of great importance and investigation for cosmic string has been done from last 20 years. There are a lot of models to detect cosmic string.But a very few are to detect the location of cosmic ...
    • Deep 3D convolutional neural network in early detection of Lung cancer 

      Hossain, Khandoker Jobayer; Rana, Md. Jewel; Ajghar, Abdullah Ali; Alam, Nur-a-taj (BRAC University, 7/22/2018)
      Early detection of lung cancer is essential for the survival of patients. Lung Cancer remains the deadliest cancer in the world. Lung cancer diagnosis is still a time consuming and long awaiting process. The oncologist is ...
    • Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models 

      Islam, Tahsin; Absar, Shahriar; Nasif, S.M. Ali Ijtihad; Mridul, Sadman Sakib (Brac University, 2021-10)
      The world is going through a severe viral pandemic which is caused by COVID- 19. People infected with this virus, experience severe respiratory illness. The virus spreads through particles of saliva or droplets from an ...
    • Deepfake detection using neural networks 

      Sakib, Sadman; Abid, Mir Tarid Al; Tiana, Nures Saba; Asha, Wajida Anwar; Huq, Syed Mahbubul (Brac University, 2021-09)
      Deepfake is a sort of arti cial intelligence that forge original image or video and create persuading images, audio and video hoaxes by utilizing two contending AI algorithms-the generator and discriminator that form a ...
    • 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 ...
    • Detection and recognition of Bangladeshi fishes using surf features and CNN classifier 

      Shuhin, Syed Adiba; Tajrin, Jannatul; Akhter, Afrin; Israth, Chowdhury (Brac University, 2018-07)
      This thesis proposes the detection and recognition of Bangladeshi local fishes using image processing. In the proposed model, we have successfully detected fishes using grass-fire algorithm along with other methods like ...
    • Exploring Alzheimer's disease prediction with XAI in various neural network models 

      Rahman, Quazi Ashikur; Shad, Hamza Ahmed; Asad, Nashita Binte; Bakshi, Atif Zawad; Mursalin, S.M Faiaz (Brac University, 2021-10)
      Using a number of Neural Network Models, we attempt to explore and explain the prediction of Alzheimer's in patients in various stages of the disease, using MRI imaging data. Alzheimer's disease(AD) often described as ...
    • Handwritten character recognition using neural network 

      Hussain, Shoumin Rafsun; Nelema, Mahima Noor; Kabir, Fahim M; Patwary, Mohammad Rasheduzzaman (Brac University, 2020-04)
      Handwritten character recognition is a process of a system to access handwritten material from various sources such as paper records, photographs, touch screen apps, etc. The identification of handwritten and electronic ...
    • 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 ...
    • Malware Detection Using Neural Network 

      Kayum, Syed Irfan; Hossain, Humaira; Tasnim, Nafisa; Paul, Arja; Rohan, Alim Aldin (Brac University, 2021-01)
      One of the great and major issues facing the Internet today is a large amount of data and files that need to be analyzed for possible malicious purposes. Malicious software also referred to as an attacker’s malware is ...
    • Modelling option prices using neural networks 

      Nasim, Ahmed Zohair; Syed, Shehran (Brac University, 2019)
      In this research, modelling of the European option prices of S&P 500 index options was carried out using Multi-layer Perceptron Neural Networks. The goal was to train the neural networks using historical data to accurately ...
    • One voice is all you need: a one-shot approach to recognize you 

      Dipto, Shahriar Rumi; Nowshin, Priata; Ahmed, Intesur; Chowdhury, Deboraj; Noor, Galib Abdun (Brac University, 2021-09)
      Human knowledge can quickly learn any unfamiliar concepts based on what they have previously learned. Keeping this in mind, researchers tested training models with limited training data in machine learning classification ...
    • Prostate cancer detection using deep learning neural network with transfer learning approach 

      Badhon, Ariful Islam Mahmud; Hasan, Md. Sadman; Haque, Md. Samiul; Pranto, Md. Shafayat Hossain; Ghosh, Saurav (Brac University, 2021-10)
      Prostate cancer is a ubiquitous form of cancer detected among men all over the world. It is currently the second leading cause of cancer death worldwide among men. Research shows that about 11% of men worldwide are ...
    • Sound classification using deep learning for hard of hearing and deaf people 

      Habib, Md.Adnan; Arefeen, Zarif Raiyan; Hussain, Arafat; Shahriyer, S.M.Rownak; Islam, Tanzid (Brac University, 2022-01)
      Our paper mainly focuses on developing an audio classification for people, who cannot hear properly, using Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). One of the many prevalent complaints from ...
    • A squeeze and excitation ResNeXt-based deep learning model for Bangla handwritten basic to compound character recognition 

      Khan, Mohammad Meraj (Brac University, 2021-08)
      With the recent advancement in artificial intelligence, the demand for handwrit- ten character recognition increases day by day due to its widespread applications in diverse real-life situations. As Bangla is the world’s ...