GS1D Yangjie

's work GS1D is a part of Yangjie's work that focuses on improving the accuracy of object detection. Specifically, this work is aimed at enhancing object detection accuracy by incorporating a deep learning approach, called Single-Shot Detection (SSD), within a wide range of data sets. Specifically, the team of researchers examined SSD's accuracy improvements by using three different datasets, including Visual Genome, the COCO dataset and the VOC dataset. The researchers achieved state-of-the-art results on the VOC dataset and improved results on the Visual Genome and COCO datasets. The team demonstrated that the proposed method could significantly reduce false positives in object detection while simultaneously improving accuracy. The proposed method relies on the incorporation of a wide range of ground truth bounding boxes across the entire image, allowing the model to better discern and classify objects that may have previously been overlooked. In addition, the researchers highlighted the importance of context when applying a deep learning model, such as SSD, to object detection tasks.