Category: 7. Maths

Dataset

We mainly use two benchmark datasets to evaluate our algorithm in UAV image object detection: VisDrone2019⁴⁹ and UAVDT⁵⁰. VisDrone2019 is a representative UAV dataset, consisting of 8599 images, containing 10 object categories: Pedestrain,…

This section presents the outcomes of the applied methodology in analyzing a decade (2011-21) of query call and yield data. The analysis was executed using a Python 3.0 script on the Google Colab platform, which was equipped with a dual Intel(R)…

To verify the proposed method, we set the training parameters and trained the model on the Objects365 (V1) dataset and the GoldG dataset (“Experimental settings”). We then designed comparative experiments on the LVIS minival and AutoMine…

This study introduces a novel approach for dental caries segmentation in panoramic radiographs utilizing the DL approach of the AI system. We depart from prior studies that relied solely on ground truth established through single radiographic…

The proposed model enhances the security in WSN by integrating advanced machine learning methodologies, including DRL, LSTM networks, and EFS. Figure 1 depicts that the commencement of the model is done by collecting heterogeneous datasets,…

In this section, the proposed CDDAT consists of two main parts. The first part introduces the process of image preprocessing. The second part is to introduce our downsampling method. Subsequently, we elaborate on the core components of CDDAT: the…

This section presents the experimental results validating the effectiveness of the proposed H-Fusion-SEG model for skin disease segmentation. The model was trained using the HAM10000 dataset and subsequently evaluated on independent test sets…