Google SSD (Single Shot Multibox Detector) was introduced in 2016 as a method for object detection that aimed to improve speed and accuracy. It was designed to perform object localization and classification in a single pass, making it suitable for real-time applications.
Google SSD (Single Shot Multibox Detector)
Google SSD (Single Shot Multibox Detector) is an object detection algorithm that identifies and classifies objects within images in a single forward pass of the network, enabling real-time detection with high accuracy.
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About Google SSD (Single Shot Multibox Detector)
Strengths of Google SSD include real-time detection capabilities and high accuracy. Weaknesses involve lower performance on smaller objects and complex scenes. Competitors include Faster R-CNN, YOLO (You Only Look Once), and RetinaNet.
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How to hire a Google SSD (Single Shot Multibox Detector) expert
A Google SSD expert must have skills in deep learning, computer vision, Python programming, TensorFlow or PyTorch frameworks, and experience with convolutional neural networks (CNNs) for object detection tasks.
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