Corn is one of the world's most important crops, critical for food, feed, and industrial applications. In 2023, corn production in China alone accounted for 41% of total crop production, highlighting ...
Shapelets and CNN are two typical approaches to model time series. Shapelets aim at finding a set of sub-sequences that extract feature-based interpretable shapes, but may suffer from accuracy and ...
Abstract: Sparse convolutional neural network (CNN) accelerators face challenges such as low utilization of processing elements (PEs), low data reuse, and high hardware sparse index addressing cost ...
Abstract: Convolutional Neural Networks (CNNs) have achieved remarkable success across various fields, particularly in image processing. However, the interference from imaging devices and external ...
Abstract: The convolutional neural network (CNN) is widely used in synthetic aperture radar (SAR) target recognition, but conventional CNN mainly adopts a single-scale convolutional kernel, resulting ...
ABSTRACT: Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers ...
1 College of Finance and Commerce, Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 ...
The config file that I used. defaults: - experiment: base_experiment - algorithm: ippo - task: meltingpot/predator_prey__orchard - model: layers/cnn - model@critic ...
Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...
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