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Understanding Padding in Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have revolutionized the field of computer vision, enabling impressive results in tasks such as image classification and object detection. In CNNs,...
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Understanding Anchor Boxes in Object Detection
Anchor boxes play a crucial role in overcoming the limitation of traditional object detection approaches, where each grid cell can detect only one object. By allowing multiple objects to be...
Data Augmentation
Deep Learning for Computer Vision: Navigating the Landscape Deep learning has made significant advancements in various domains such as computer vision, natural language processing, speech recognition, online advertising, and logistics....
The Importance of Data Augmentation in Computer Vision
Data augmentation is a crucial technique used to improve the performance of computer vision systems. In the realm of computer vision, where the input is an image composed of countless...
Transfer Learning: Accelerating Computer Vision Applications with Pre-Trained Models
When building computer vision applications, leveraging pre-trained models can significantly speed up the development process and yield faster progress. Instead of training a neural network from scratch, you can download...
EfficientNet: Scaling Neural Networks for Optimal Performance
In today’s rapidly evolving technological landscape, developing neural networks that can efficiently adapt to different devices and computational resources is crucial. This is where EfficientNet comes into play. EfficientNet is...