Training Faster R-CNN Using TensorFlow’s Object Detection API with a Custom Dataset

Training Faster R-CNN Using TensorFlow’s Object Detection API with a Custom Dataset

Training Faster R-CNN Using TensorFlow’s Object Detection API with a Custom Dataset. Step-by-step tutorial. An extremely helpful article. You will definitely regret skipping it.

Step-by-step tutorial to train a faster R-CNN for object detection with TensorFlow using a custom dataset

ecently, object detection has continued to evolve from its current state, and due to its technology, it can be found across almost every technological platform. Whether it is through image classification, recognition, or localization, these are all based on object detection.

Convolutional neural networks (CNNs) can bring together many object recognition and classification techniques together by incorporating deep learning and computer vision methods. In computer vision,** convolutional neural networks,** as the name suggests, apply a convolution layer in each pixel image in a dataset.

Due to computer vision and deep learning fundamentals in its primary structure, CNNs obtain a different output layer step-by-step by moving the filter we specify onto an image.

deep-learning computer-vision programming machine-learning artificial-intelligence

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