Now showing items 21-36 of 36

    • Heart disease prediction system 

      Amit, Tayab Al Azad; Fullkoli, Raida Nawar; Palit, Niloy; Nafisa, Farhana Khan; Binoy, MD Muntakim Ahmed (Brac University, 2022-01)
      [1]According to the World Health Organization (WHO), 17.9 million people die each year due to cardiovascular diseases (CVDs), almost 31% of all deaths worldwide. This single piece of evidence is strong enough to describe ...
    • Integration of handcrafted and deep neural features for Melanoma classification 

      Rahman, Mohammad Saminoor; Hossain, Md. Jubayer; Islam, Siful; Kabir, Md. Nafiul; Sujon, Md. Kamrul Hasan (Brac University, 2021-09)
      Deep neural networks (DNNs) are widely utilized to automate medical image in- terpretation in many forms of cancer diagnosis and to support medical specialists with fast data processing. Although man-made characteristics ...
    • 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 ...
    • Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet 

      Promita, Samanta Tabassum; Biswas, Simon Abhijet; Mozumder, Nisat Islam; Taharat, Mamur (Brac University, 2022-01)
      Due to our unhealthy diets and the consumption of enhanced cholesterol in our daily lives, our health has become vulnerable and at risk of different types of cardiac diseases. The most common of them is Myocardial ...
    • 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 ...
    • Real-time fire detection based on feature analysis using enhanced color segmentation and novel foreground extraction 

      Khan, Rubayat Ahmed (Brac University, 2017-07)
      This research proposes two effective real time fire detection techniques, based on video processing. The former technique is restricted to indoor conditions only while the later does not have such constraints. Both the ...
    • 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 ...
    • A supervised machine learning approach to predict vulnerability to drug addiction 

      Faisal, Fahim; Shahriar, Arif; Mahmud, Sohan Uddin; Shuvo, Rakibul Alam (Brac University, 2019-08)
      There are signi cant amount of di erences between an addicted and non-addicted person on their social and familial behavior. In our thesis we tried to nd out the characteristics of a person related to his social and ...
    • Towards solving perception based autonomous driving assistant system 

      Hossain, Md. Arafat; Rahman, Md. Sazidur; Islam, Md. Jisan Bin; Bhuiyan, Sazzad Alam (Brac University, 2021-09)
      This thesis scrutinizes the problem of perception in the self-driving car system. Selfdriving car is the face of the future and the decade’s research focus. Tech giants like Google, Uber, Tesla, Commai, Intel MobilEye ...
    • Urban sound classification using convolutional Neural Network and long short term memory based on multiple features 

      Das, Joy Krishan; Ghosh, Arka; Pal, Abhijit Kumar; Dutta, Sumit (Brac University, 2020-04)
      There are many sounds all around us and our brain can easily and clearly identify them. Furthermore, our brain processes the received sound signals continuously and provides us with relevant environmental knowledge. ...
    • Visual object classification from fMRI data 

      Newaz, Syed Mishar; Taseeb, Taslim Ahmed; Haque, Abdullah Nurul (Brac University, 2022-01)
      Computing devices were once limited in just calculating arithmetic. Whereas, in modern computing, complex task like object classi cation or recognition has become so popular that even our smart devices cannot be thought ...
    • X-Ray classification to detect COVID-19 using ensemble model 

      Solaiman, Ishmam Ahmed; Sanjana, Tasnim Islam; Sobhan, Samila; Maria, Tanzila Sultana (Brac University, 2021-06)
      Diagnosis with X-Rays and other forms of medical images has soared to new heights as an alternative visual Covid infection detector. Radiographic images, primarily CT scans and X-Rays images play massive roles in assisting ...