Now showing items 1-20 of 40

    • 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 ...
    • Brain hemorrhage detection using hybrid machine learning algorithm 

      Iqbal, Khondoker Nazia; Azad, Istinub; Emon, Md. Imdadul Haque; Amlan, Nibraj Safwan; Aporna, Amena Akter (Brac University, 2022-01)
      Machine learning (ML) helps computers learn and program data without humans’ help. According to data scientists, machine learning can extract 60% high-quality information, reduce the cost up to 46%, and increase operation ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • Computer vision-based Bengali sign language to text generation 

      Tazalli, Tonjih; Liya, Sumaya Sadbeen; Aunshu, Zarin Anan; Hossain, Magfirah; Mehjabeen, Zareen (Brac University, 2022-01)
      In the whole world, around 7% of people have hearing and speech impairment problems. They use sign language as their communication method. People from various countries use a variety of sign languages. As an example, ...
    • 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 learning based predictive analytics for decentralized content caching in hierarchical edge networks 

      Chakraborty, Dhruba; Rabbi, Mahima; Hossain, Maisha; Khaled, Saraf Noor; Oishi, Maria Khanom (Brac University, 2022-01)
      Content centric network is a state-of-the-art networking architecture for content distribution and content caching. However, it is inefficient to cache every content in each network device. The modern edge computing ...
    • 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 ...
    • Diabetic retinopathy detection and classification by using deep learning 

      Hossain, Shahriar; Evan, Md. Nurusshafi; Farhin, Fariya Zakir; Nabil, Mashrur Karim; Sadman, Sameen (Brac University, 2022-01)
      Eyes are the most sensitive part of a human being and it is one of the most challenging tasks for a computer-aided system to classify its diseases. Many visionthreatening diseases such as, Glaucoma and Diabetic Retinopathy ...
    • 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 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 ...
    • Epileptic seizure prediction using bandpass filtering and convolutional neural network 

      Rahman, Tasnia; Mustaqeem, Nabiha; Priyo, Jannatul Ferdous Binta Kalam; Shahariar, Ahnaf; Sharmin, Shaila (Brac University, 2022-01)
      Epilepsy, a chronic neurological disorder, causes seizure- a fast, uncontrollable electrical disturbance in the brain. Seizures that last for a long time might result in memory loss, weariness, photo sensitivity, paralysis, ...