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U-Net for Semantic Segmentation

U-Net for Semantic Segmentation

As the field of computer vision grows, increasingly efficient tools are being built to more finely parse visual information. Deep learning for computer vision and Convolutional Neural Networks (CNNs) are the primary technologies being...

An Introduction to Transfer Learning

An Introduction to Transfer Learning

As we strive to create machines that can handle complex tasks, deep learning is increasingly coming into the spotlight. Because many of the tasks we want our machines to perform are intuitive...

Best GPU for Deep Learning

Best GPU for Deep Learning

Creating a Deep Learning (DL) model involves training Artificial Neural Networks (ANN) to perform various tasks. This process usually includes exposing the model to thousands or millions of datasets. This type of...

An Introduction to Deep Reinforcement Learning

An Introduction to Deep Reinforcement Learning

Deep reinforcement learning is a promising combination between two artificial intelligence techniques: reinforcement learning, which uses sequential trial and error to learn the best action to take in every situation, and deep...

An Insight into YOLO Deep Learning

An Insight into YOLO Deep Learning

Object detection algorithms enable many advanced technologies and are a primary research focus for many industries from transportation to healthcare. For example, a common use for object detection algorithms is to implement...

Object Tracking Simplified

Object Tracking Simplified

Object tracking is a field within computer vision that involves tracking objects as they move across several video frames. In this article, we’ll address the difference between object tracking and object detection,...

Super-Resolution Deep Learning

Super-Resolution Deep Learning

The image remastering approach known as Super-Resolution (SR) has numerous applications in many fields such as medical imaging in healthcare, autonomous driving systems and analyzing security footage. SR technologies have been rapidly growing since the...

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