paper-with-me

홈 › Papers

Application of Convolutional Neural Network for Image Classification on Pascal VOC Challenge 2012 dataset

2016-07-13 · Suyash Shetty

In this project we work on creating a model to classify images for the Pascal VOC Challenge 2012. We use convolutional neural networks trained on a single GPU instance provided by Amazon via their cloud service Amazon Web Services (AWS) to classify images in the Pascal VOC 2012 data set. We train multiple convolutional neural network models and finally settle on the best model which produced a validation accuracy of 85.6% and a testing accuracy of 85.24%.

📄 PDF Abstract BibTeX arXiv:1607.03785

Code (0)

등록된 구현이 없습니다.

Tasks

General ClassificationGPUimage-classificationImage Classification

Similar Papers 제목 키워드 기반

Learning and Transferring Mid-Level Image Representations using Convolutional Neural Networks

2014-06-01 · CVPR 2014 6 · Maxime Oquab, Leon Bottou, Ivan Laptev, Josef Sivic

Convolutional neural networks (CNN) have recently shown outstanding image classification performance in the large- scale visual recognition challenge (ILSVRC2012). The success of CNNs is attributed to their ability to le…

Action ClassificationAction LocalizationClassificationGeneral Classification+3

Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks

2017-01-17 · Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Arbeláez, Luc van Gool

We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs). COB is computational…

Boundary DetectionContour Detectionimage-classificationImage Classification+6

Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation

2017-07-26 · Sharif Amit Kamran, Ali Shihab Sabbir

Semantic Segmentation using deep convolutional neural network pose more complex challenge for any GPU intensive task. As it has to compute million of parameters, it results to huge memory consumption. Moreover, extractin…

GPUImage SegmentationScene SegmentationSegmentation+1

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

2014-06-18 · Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224x224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrary s…

General Classificationimage-classificationImage Classificationobject-detection+2

Fully Convolutional Networks for Semantic Segmentation

2016-05-20 · CVPR 2015 · Evan Shelhamer, Jonathan Long, Trevor Darrell

Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, improve on the previous best result in semant…

Real-Time Semantic SegmentationScene SegmentationSegmentationSemantic Segmentation+1