Listar 2023 por tema 

Listar2023 por tema "convolutional neural network (CNN)"

Mostrando ítems 1-4 de 4

    • COVID-19 Disease Prediction Using Weighted Ensemble Transfer Learning 

      Kumar Roy, Pradeep; Singh, Ashish (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 03/2023)
      Health experts use advanced technological equipment to find complex diseases and diagnose them. Medical imaging nowadays is popular for detecting abnormalities in human bodies. This research discusses using the Internet ...

    • Deep Learning Assisted Medical Insurance Data Analytics With Multimedia System 

      Zhang, Cheng; Vinodhini, B.; Muthu, Bala Anand (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2023)
      Big Data presents considerable challenges to deep learning for transforming complex, high-dimensional, and heterogeneous biomedical data into health care data. Various kinds of data are analyzed in recent biomedical research ...

    • Deep Transfer Learning-Based Automated Identification of Bird Song 

      Das, Nabanita; Padhy, Neelamadhab; Dey, Nilanjan; Bhattacharya, Sudipta; Tavares, Joao Manuel R. S. (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 12/2023)
      Bird species identification is becoming increasingly crucial for avian biodiversity conservation and assisting ornithologists in quantifying the presence of birds in a given area. Convolutional Neural Networks (CNNs) are ...

    • Synthetic Aperture Radar Automatic Target Recognition Based on a Simple Attention Mechanism 

      Ukwuoma, Chiagoziem Chima; Zhiguang, Qin; Tienin, Bole W.; Yussif, Sophyani B.; Ejiyi, Chukwuebuka Joseph; Urama, Gilbert C.; Ukwuoma, Chibueze D.; Chikwendu, Ijeoma Amuche (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 12/2023)
      A simple but effective channel attention module is proposed for Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR). The channel attention technique has shown recent success in improving Deep Convolutional ...