Now showing items 1-9 of 9

    • An approach to detect epileptic seizure using XAI and machine learning 

      Bijoy, Emam Hasan; Rahman, Md. Hasibur; Ahmed, Sabbir; Laskor, Md. Shifat (Brac University, 2022-05)
      One of the most common neurological disorder in health sector is Epileptic Seizure (ES) which is occurred by sudden repeated seizures. Hitherto more than 50 million people in the whole world are suffering from Epileptic ...
    • Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI 

      Tasnim, Anika; Hossain, Nigah; Tabassum, Sabrina; Parvin, Nazia (Brac University, 2022-05)
      The internet of things is one of today’s most revolutionary technologies. Because of its pervasiveness, increasing network connection capacity, and diversity of linked items, the internet of things (IoT) is adaptable and ...
    • A decentralized learning-based approach to classify colorectal cancer using Deep Learning Leveraging XAI 

      Mubin, Kazi Ehsanul; Arthi, Noshin Tabassum; Rahman, Junayed; Rafi, G. M.; Sheja, Tahsina Tanzim (Brac University, 2022-05)
      Convolutional Neural Networks (CNN)-based automated approaches are vastly utilised to anticipate and diagnose cancer, saving time and reducing mistakes. Deep Learning (DL) CNN methods use a variety of probabilistic and ...
    • Decipherable classification of glaucoma using deep neural network leveraging XAI 

      Chayan, Touhidul Islam; Islam, Anita; Tonny, Anika Rahman; Rahman, Eftykhar (Brac University, 2022-01-18)
      Glaucoma is the second driving reason for partial or complete blindness among all the visual deficiencies which mainly occurs because of excessive pressure in the eye due to anxiety or depression which damages the optic ...
    • Demystifying machine learning models for IOT attack detection with explainable AI 

      Muna, Rabeya Khatun; Maliha, Homaira Tasnim; Hasan, Mahedi (Brac University, 2021-09)
      Internet of things (IoT) dramatically is changing our lives with its newly invented devices and applications which leads to various emerging cybersecurity challenges or threats. The rapid growth of IoT arouses security ...
    • 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 ...
    • Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI 

      Athina, Fahima Hasan; Sara, Sadaf Ahmed; Tabassum, Nishat; Sarwar, Quazi Sabrina; Jannat Era, Mun Tarin (Brac University, 2022-05)
      This research work aims to show a comparative analysis among four different deep learning approaches to classify three rare but deadly skin diseases namely Stevens Johnson Syndrome, Erythema Multiforme and Bullous Pemphigoid. ...
    • PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework 

      Rahman, Tahsinur; Ahmed, Nusaiba; Monjur, Shama; Haque, Fasbeer Mohammad; Kabir, Naweed (Brac University, 2023-01)
      As the world is moving more and more towards a digital era, a great majority of data is transferred through a famous format known as PDF. One of its biggest obstacles is still the age-old problem: malware. Even though ...
    • Plant leaf disease identification 

      Hasan Mahin, Mohammad Rakibul; Moonwar, Waheed; Rayhan Chy, Md. Shamsul; Shahriar, Md. Fahim; Rafi, Fahim Faisal (Brac University, 2023-01)
      Agriculture has consistently been an essential component of our day-to-day life over the centuries. Because of its contribution to our country’s revenue, the importance of agriculture has been steadily growing over the ...