In the realm of training models for object detection and segmentation, with a particular focus on maximizing performance on the Mini COCO 2014 dataset, this research presents a study on improving object detection and segmentation accuracy using sophisticated deep learning models. The objective is to maximize object detection performance while minimizing resource consumption and error rates on mid-range hardware. In order to increase overall accuracy and more accurately capture object boundaries, the method entails fine-tuning deep learning models such as Mask R-CNN and DETR.........

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A MIMO (Multiple input multiple output) antenna system with two elements, which are designed with coupled grounds for UWB application is presented. The MIMO antenna system consists of Butterfly shaped patches with circular slots at the centre and a defected ground structure (DGS) with inverted F-shaped stub to enhance antenna impedance matching. The operating frequency is taken from 2 to 14 GHz. This antenna's area is 35mm × 50mm and is mounted on single layer substrate of FR-4 with 1.6mm thickness and dielectric constant ↋r =4.4. The observations of antenna are showcased with the help of S11, ECC, VSWR, DG and TARC. The results are analysed which shows that the designed two element MIMO antenna array can effectively be utilized for UWB applications.

Keywords: MIMO antennas, Ultra-Wideband (UWB) Defective Ground Structure (DGS), Envelop Correlation Coefficient (ECC), Voltage Standing Wave Ratio (VSWR), Diversity Gain (DG), Total Active Reflection Coefficient (TARC).

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