renowned for its real-time object detection capabilities, and exploring various deep learning architectures. Kitchen utensil images are preprocessed, augmented, and trained using YOLOv5 with multiple ...

Self supervised autoencoder approach aimed towards improving the detections of SOTA object detector YOLOv5 by detecting and re-constructing multiple objects in an image. This approach effectively ...

This research study demonstrates a deep learning method for multi-object detection. The study assesses YOLO's performance in identifying multiple objects in cluttered and complicated settings and ...

Real Time object detection ... previous YOLOv5 versions. There is no official paper released yet and also many controversies are happening about its name. Now Let’s see some coding example that was ...

As we all know, the key to object tracking and behavior analysis is object detection. Therefore, underwater object detection technology has become an important research direction based on deep ...

This project aims to develop deep learning models for the detection and classification of brain tumors using MRI images ... Additionally, a YOLOv5 model is trained on a brain tumor dataset from ...

Therefore, an object detection algorithm used in USVs should have high detection s peed and accuracy. In this paper, a YOLOv5 lightweight object detection algorithm using a Ghost module ... algorithm ...

The novel technique is based on the VarifocalNet deep-learning object detection ... other detection methods were tested on the same database: RetinaNet, DDH-YOLOv5, Faster GG R-CNN, Cascade ...