Erratum to: Refining deep convolutional features for improving fine-grained image recognition
نویسندگان
چکیده
Erratum Upon publication of the original article [1], it was noticed that there were several blanks in the Table 5 and the footnote of the Table 5, ‘The 'n/a' entries in the table means that bounding box or part annotation is not used.’ was incorrectly given as ‘The 'n/a' entries in the table means that the results are not available.’ This has now been acknowledged and corrected in this erratum. This has now been incorporated in the new Table 5 shown below.
منابع مشابه
Integrating Scene Text and Visual Appearance for Fine-Grained Image Classification with Convolutional Neural Networks
Text in natural images contains rich semantics that are often highly relevant to objects or scene. In this paper, we focus on the problem of fully exploiting scene text for visual understanding. The main idea is combining word representations and deep visual features into a globally trainable deep convolutional neural network. First, the recognized words are obtained by a scene text reading sys...
متن کاملBrain Age Prediction Based on Resting-State Functional Connectivity Patterns Using Convolutional Neural Networks
Brain age prediction based on neuroimaging data could help characterize both the typical brain development and neuropsychiatric disorders. Pattern recognition models built upon functional connectivity (FC) measures derived from resting state fMRI (rsfMRI) data have been successfully used to predict the brain age. However, most existing studies focus on coarse-grained FC measures between brain r...
متن کاملBird Species Categorization Using Pose Normalized Deep Convolutional Nets
We propose an architecture for fine-grained visual categorization that approaches expert human performance in the classification of bird species. Our architecture first computes an estimate of the object’s pose; this is used to compute local image features which are, in turn, used for classification. The features are computed by applying deep convolutional nets to image patches that are located...
متن کاملA hybrid EEG-based emotion recognition approach using Wavelet Convolutional Neural Networks (WCNN) and support vector machine
Nowadays, deep learning and convolutional neural networks (CNNs) have become widespread tools in many biomedical engineering studies. CNN is an end-to-end tool which makes processing procedure integrated, but in some situations, this processing tool requires to be fused with machine learning methods to be more accurate. In this paper, a hybrid approach based on deep features extracted from Wave...
متن کاملDeep Attributes from Context-Aware Regional Neural Codes
Recently, many researches employ middle-layer output of convolutional neural network models (CNN) as features for different visual recognition tasks. Although promising results have been achieved in some empirical studies, such type of representations still suffer from the well-known issue of semantic gap. This paper proposes so-called deep attribute framework to alleviate this issue from three...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- EURASIP J. Image and Video Processing
دوره 2017 شماره
صفحات -
تاریخ انتشار 2017