Browsing by Subject "Grad-CAM"

Now showing items 1-5 of 5

    • Deep Learning based Medicinal Plants Leaf Recognition 

      Mahalanabish, Tonusri (Brac University, 2022-09)
      Plants assume a significant part in Earth’s nature by giving food, cover and keeping a solid environment.These plants contain some significant therapeutic qualities. Due to having fewer negative side effects and being ...

    • Deep learning-based waste classification system for efficient waste management 

      Nakib, Abdullah Al; Talukder, Md. Nayem; Majumder, Chinmoy; Biswas, Soptorshi; Hassan, Jabid (Brac University, 2021-10)
      A smart waste management system plays a vital role in building cleanliness, hygienic, and healthier living for the inhabitants of a city. However, the inherent problems of the waste management system are still a matter ...

    • Explainable breast cancer detection from Histopathology images using transfer learning and XAI 

      Farabi, Farhan; Hossen, Farhan; Monsur, Farhan; Hossain, Mir Araf; Hasan, Md. Mohibul (Brac University, 2023-01)
      Nowadays, research on many diseases such as cancer has been ongoing to determine how to reduce and minimise the effect. There are many characteristics of cancer that can be identified by their consistent cell proliferation ...

    • An interpretable transformer based approach to classify Malaria from blood cell images 

      Islam, Mehafuza; Al Mamun, S.M. Abdulla (Brac University, 2023-01)
      Malaria is a disease that can be fatal, and it is spread through the bite of the female Anopheles mosquito. The life of the sufferer is put in jeopardy as a result of the pres ence of numerous plasmodium parasites, which ...

    • Violent activity detection through surveillance camera using deep learning 

      Miah, Parvez; Haque, Abrar Ahbabul; Imran, Abdullah Al; Hassan, MD. Radip; Rahman, Rafiur (Brac University, 2023-01)
      Surveillance camera systems have been implemented in most parts of the world to combat the rising rate of criminal activities. In the hopes of making public places safer for everyone, computer vision has also aided in ...