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What is ROS? A Comprehensive Overview In 4 Points

April 17, 2021No Comments

Introduction Technology’s purpose these days is to revolutionize in a way to make human tasks simple with every minute. Robots had been introduced to not only help humans in doing work efficiently but also remove any restrictions which humans face while doing certain jobs, and this is the reason major companies are entering into the […]

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Introduction Technology’s purpose these days is to revolutionize in a way to make human tasks simple with every minute. Robots had been introduced to not only help humans in doing work efficiently but also remove any restrictions which humans face while doing certain jobs, and this is the reason major companies are entering into the […]

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AlexNet: An Important Architecture In 3 Easy Points

Introduction Like human learning, machine learning also needs to be upgraded from time to time. An ImageNet competition took place in 2012, and it was won by a student named Alex, and that was the birth of alexnet. An alexnet architecture consists of convolutional layers, normalization layers, fully connected layers, softmax layers, and max-pooling layers. Thus, before […]

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Introduction Like human learning, machine learning also needs to be upgraded from time to time. An ImageNet competition took place in 2012, and it was won by a student named Alex, and that was the birth of alexnet. An alexnet architecture consists of convolutional layers, normalization layers, fully connected layers, softmax layers, and max-pooling layers. Thus, before […]

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Fully Convolutional Network (FCN): A Basic Overview In 2021

Introduction FCNs, or Fully Convolutional Networks, are a form of architecture that is primarily used for semantic segmentation. Convolution, pooling, and upsampling are the only locally linked layers they use. Since dense layers aren’t used, there are fewer parameters (making the networks faster to train). It also means that an FCN can handle a wide range […]

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Introduction FCNs, or Fully Convolutional Networks, are a form of architecture that is primarily used for semantic segmentation. Convolution, pooling, and upsampling are the only locally linked layers they use. Since dense layers aren’t used, there are fewer parameters (making the networks faster to train). It also means that an FCN can handle a wide range […]

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