Ship Classification in TerraSAR-X Images With Convolutional Neural Networks

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Classification of Time-Series Images Using Deep Convolutional Neural Networks

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifie...

متن کامل

Classification of breast cancer histology images using Convolutional Neural Networks

Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods desig...

متن کامل

Classification of Photo and Sketch Images Using Convolutional Neural Networks

In this study we propose a Convolutional Neural Network(CNN) which can classify hand drawn sketch images. Though CNN is known to be very effective on classification of realistic images, there are few studies on CNN dealing with nonphotorealistic images and even more images those types are mixing. Classifying non-photorealistic images is difficult mainly because there are no large datasets. In t...

متن کامل

Scene Classification with Deep Convolutional Neural Networks

The use of massive datasets like ImageNet and the revival of Convolutional Neural Networks (CNNs) for learning deep features has significantly improved the performance of object recognition. However, performance at scene classification has not achieved the same level of success since there is still semantic gap between the deep features and the high-level context. In this project we proposed a ...

متن کامل

ImageNet Classification with Deep Convolutional Neural Networks

The intended goal of the experiments was to create a deep, convolutional network that uses supervised learning to achieve better (lower) error rates than the rates previously observed, to identify images, on a highly challenging dataset. The parameters used for judging if the CNN is able to recognise the object is given by “Top-1” and “Top-5” predictions made – that is the top prediction made, ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Journal of Oceanic Engineering

سال: 2018

ISSN: 0364-9059,1558-1691,2373-7786

DOI: 10.1109/joe.2017.2767106