Based on this observation, they proposed a new scaling method that uniformly scales all dimensions of depth, width and resolution of the network. They used the neural architecture search to design a ...

Researchers at Soongsil University (Korea) published “A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration.” Abstract: “Over the past decade, deep-learning-based ...

As this convolutional neural network has 19 layers in its architecture, it was named VGG-19. This model was proposed to reduce the number of parameters in a convolutional neural network with improved ...

We propose a statistical learning-based traffic speed estimation method that uses sparse vehicle trajectory information. Using a convolutional encoder-decoder based architecture, we show that a well ...

Paper Summary: U-Net: Convolutional Networks for Biomedical Image Segmentation, MICCAI 2015 Olaf Ronneberger, Philipp Fischer, and Thomas Brox [DOI] In this paper, the authors proposed a fully ...

We test and analyze the performance of the convolutional network both unconditionally and conditionally for financial time series forecasting using the Standard & Poor’s 500 index, the volatility ...

Applied region-based convolutional neural networks (Faster-RCNN) to damage detection in real-time. Note: This project is mostly an application for masonry historic structures using fine-tuned deep ...

The breakthrough in the neural network field for vision was Yann LeCun’s 1998 LeNet-5, a seven-level convolutional neural network (CNN) for recognition of handwritten digits digitized in 32×32 ...