Vision-Based Intelligent Robot Grasping Using Sparse Neural Network

Description

In the modern era of Deep Learning, network parameters play a vital role in models efficiency but it has its own limitations like extensive computations and memory requirements, which may not be suitable for real time intelligent robot grasping tasks. Current research focuses on how the model efficiency can be maintained by introducing sparsity but without compromising accuracy of the model in the robot grasping domain. More specifically, in this research two light-weighted neural networks have

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