This study evaluates YOLOv12 using a globally sourced traffic dataset that includes varied weather conditions, lighting scenarios, and geographic locations. The model demonstrates strong performance ...

Traditional methods in machine learning for detecting traffic lights and classification are replaced by the recent enhancements of deep learning object detection methods by success of building ...

Custom Object Detection Using Tensorflow Object Detection API using pre trained ssd_mobile_net model . Downloaded the model from object detection module of tensorflow and then further customized it to ...

Object detection forms an important area of research where the efforts are still being put forth to improve the accuracy of detection. Several approaches have been made which also include R-CNN and ...

Collect a few hundred images that contain your object - ideal is 500+. Annotate/label the images, ideally with a program LabelImg/RectLabel - to create an XML file. Split this data into train/test ...

Google announced support for TensorFlow 2 (TF2) in the TensorFlow Object Detection (OD) API. The release includes eager-mode compatible binaries, two new network architectures, and pre-trained ...