Images obtained in this way represent a high-quality source of information and could be further used as an input dataset for various object detection and classification algorithms. In recent years, ...

our object detection model reached 87% accuracy. A sample prediction at the end of the training is as follows; The image of the class predicted as a result of the classification was sized to 70% of ...

series of models in the lung CT image object detection task is compared in terms of algorithms, and different versions of YOLOv5, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are examined for lung cancer ...

The maritime object detection includes two tasks, i.e., classification and positioning of ships. A robust object detection algorithm should not only consider the detection speed, but also consider the ...

Abstract: To address the challenge of effectively classifying and recycling construction and demolition waste (CDW), this study proposes a lightweight object detection algorithm ... accuracy and ...

For eg- If your image name is test.jpg, then put your image in the directory named Test and then run- ...

Synspective Inc., a provider of Synthetic Aperture Radar (SAR) satellite data and analytics solutions, is pleased to announce the launch of its Object Detection and Classification (ODC) solution, ...

is pleased to announce the launch of its Object Detection and Classification (ODC) solution, designed to enhance the accuracy and reliability of monitoring vessels and aircraft. This solution ...