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Stride in CNNs: The key tweak that matters
In this video, we will understand what is Stride in Convolutional Neural Network. While performing Convolution operation on ...
Learn With Jay on MSN
How Stride in CNNs Impacts Model Performance?
In this video, we will understand what is Stride in Convolutional Neural Network. While performing Convolution operation on an image, we move our filter by 1 pixel. It is called having the stride = 1.
Abstract: The Siamese network architecture has been applied by deep learning practitioners to find similarities between images. In the domain of autonomous driving, this network configuration has ...
Abstract: Fast Fourier Transformation (FFT) has been widely recognized as an effective method for reducing the computational density of convolutional neural networks (CNNs). However, existing ...
A Column Streaming-Based Convolution Engine and Mapping Algorithm for CNN-based Edge AI Accelerators
Abstract: Edge AI accelerators have been emerging as a solution for near customers' applications in areas such as image recognition sensors, remote sensing satellites, robotics, wearable devices, and ...
Abstract: This paper presents a new deformable convolution-based video frame interpolation (VFI) method, using a coarse to fine 3D CNN to enhance the multi-flow prediction. This model first extracts ...
Abstract: Convolutional neural networks (CNNs) for hyperspectral image (HSI) classification have generated good progress. Meanwhile, graph convolutional networks (GCNs) have also attracted ...
Abstract: As more and more robots are envisioned to cooperate with humans sharing the same space, it is desired for robots to be able to predict others' trajectories to navigate in a safe and ...
Abstract: Convolutional Neural Networks (CNNs) have emerged as a critical tool in computer vision, and FPGA-based acceleration has become a primary approach for the efficient deployment and ...
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