Browsing by Author "Abrar, Mohammed Abid"

Now showing items 1-5 of 5

    • A comparative analysis of emotion recognition using EEG signals with a channel selection technique 

      Riduan, Jonayed Ahmed; Mahjabin, Most.; Mim, Nadia Tasnim; Islam, Ridwane-ul; Rana, Md. Shahriar Rahman (Brac University, 2021-01)
      Emotion can be defined as the neurophysiological changes people experience due to significant internal or external occasions. This is a mental condition that can a↵ect a person’s behavior, mood, way of life, and relationship ...

    • A comparative performance analysis of accident anticipation with deep learning extractors 

      Mostak, Alfi Mashab; Neha, Nayna Jahan; Mohiuddin, Azwaad Labiba; Tabassum, Adiba (Brac University, 2022-09-29)
      Accident anticipation has become a major focus to avert accidents or to minimize their impacts. Over the years, several network systems are being developed and applied in self-driving technology. Despite the fact that ...

    • 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 ...

    • DWT based transformed domain feature extraction approach for epileptic seizure detection 

      Mostafa, Mahajabin; Samin, Mohtasim Abrar; Hassan, Nabila Bintey; Nibras, Saiara Zerin; Rahman, Samir (Brac University, 2021-09)
      Epileptic seizure is a neurological disorder that is prevalent in both males and females of all age ranges. Detection of epileptic seizure serves as an important role for epileptic patients as it allows the initiation ...

    • Identifying genes with location dependent noise variance in spatial transcriptomics data 

      Abrar, Mohammed Abid (Brac University, 2022-12)
      Spatial transcriptomics (ST) holds the promise to identify the existence and extent of spatial variation of gene expression in complex tissues. Such analyses could help identify gene expression signatures that distinguish ...