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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 ...
IEEE

Modified CNN VoxNet Based Depthwise Separable Convolution for Voxel-Driven Body Orientation Classification

Abstract: In this research, LiDAR sensor technology introduces a new representation of point cloud data for tasks in 3D object recognition. Point clouds provide rich information that can be utilized ...
IEEE

Comparative Analysis of Deep Learning-Based Feature Extractors for Change Detection in Automotive Radar Maps

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 ...
IEEE

Low-Overhead CNN Acceleration via FFT-based Circular Convolution and Partially Pipelined Dataflow

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 ...
IEEE

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 ...
IEEE

Enhancing Deformable Convolution Based Video Frame Interpolation with Coarse-To-Fine 3d Cnn

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 ...
IEEE

Attention Multihop Graph and Multiscale Convolutional Fusion Network for Hyperspectral Image Classification

Abstract: Convolutional neural networks (CNNs) for hyperspectral image (HSI) classification have generated good progress. Meanwhile, graph convolutional networks (GCNs) have also attracted ...
IEEE

Noticing Motion Patterns: A Temporal CNN With a Novel Convolution Operator for Human Trajectory Prediction

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 ...
IEEE

FPGA-Based CNN Acceleration Algorithm Design Using Diffused Convolution and Pruning Techniques

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 ...