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  • Open Access

    ARTICLE

    Symbiotic Organisms Search with Deep Learning Driven Biomedical Osteosarcoma Detection and Classification

    Abdullah M. Basahel1, Mohammad Yamin1, Sulafah M. Basahel2, Mona M. Abusurrah3, K.Vijaya Kumar4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 133-148, 2023, DOI:10.32604/cmc.2023.031786 - 06 February 2023

    Abstract Osteosarcoma is one of the rare bone cancers that affect the individuals aged between 10 and 30 and it incurs high death rate. Early diagnosis of osteosarcoma is essential to improve the survivability rate and treatment protocols. Traditional physical examination procedure is not only a time-consuming process, but it also primarily relies upon the expert’s knowledge. In this background, the recently developed Deep Learning (DL) models can be applied to perform decision making. At the same time, hyperparameter optimization of DL models also plays an important role in influencing overall classification performance. The current study… More >

  • Open Access

    ARTICLE

    A Hybrid Approach of TLBO and EBPNN for Crop Yield Prediction Using Spatial Feature Vectors

    Preeti Tiwari1, *, Piyush Shukla1

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 45-58, 2019, DOI:10.32604/jai.2019.04444

    Abstract The prediction of crop yield is one of the important factor and also challenging, to predict the future crop yield based on various criteria’s. Many advanced technologies are incorporated in the agricultural processes, which enhances the crop yield production efficiency. The process of predicting the crop yield can be done by taking agriculture data, which helps to analyze and make important decisions before and during cultivation. This paper focuses on the prediction of crop yield, where two models of machine learning are developed for this work. One is Modified Convolutional Neural Network (MCNN), and the… More >

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