Image Classification
DECODE:Deep Confidence Network for Robust Image Classification
... Abstract —The recent years have witnessed the success of deep convolutional neural networks for image classification and many related tasks. It should be pointed out that the existing training strategies ...
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Automatic Image Classification for Planetary Exploration
... Since the early days of neural networks, researchers have arranged an ensemble of neural net- works in a simple voting scheme to improve performance [5]. Networks with a collection of many paths can have ensemble-like ...
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No-reference image quality metric based on image classification
... In this article, we propose a new NR blocking metric and a new NR blur metric based on human visual sensi- tivity, and we also propose a NR metric based on image classification. The proposed blocking metric ...
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A Survey on Medical Image Classification Techniques
... an image by human physician, an automated technique will provide valuable assistance for ...medical image analysis has been on automated image classification ...multi-class ...
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Zero-shot Image Classification
... input image and then reconstruct it, through which discriminative features are ...performance. Classification The most straight forward classifier could be the NN classifier ...with image-to-class ...
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Automatic Hierarchical Color Image Classification
... All the above works have only focused on visual fea- tures. Gevers et al. [10] try to integrate visual and textual features for web image classification. The textual informa- tion extracted from HTML tags ...
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Image Classification in Remote Sensing
... “Image Classification”. Image Classification had made great progress over the past decades in the following four areas: (1) producing land cover map at regional and global scale; (2) ...
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Advances in hyperspectral image classification
... hyperspectral image classification: kernel methods and support vector machines (SVM) [2], sparse multinomial logistic regression [6], neural networks [7] and Bayesian ap- proaches like relevance vector ...
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Color Image Classification and Retrieval using Image mining Techniques
... Mining Image data is one of the essential features in the present ...scenario. Image data is the major one which plays vital role in every aspect of the systems like business for marketing, hospital for ...
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CNN based Image Classification Model
... The introduction of Convolutional Neural Network has changed the way image classification problem has been visualized. The ImageNet competition plays a crucial role in the development of ...
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Product Image Classification Techniques
... preferences. Classification is a machine learning technique that could assist in increasing scalability, creating dynamic user profiles and ultimately improve recommendation ...of image ...
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An Improved Image Retrieval System using Image Classification
... An image retrieval system is a computer system for browsing, searching and retrieving image using the actual content of image like visual features of an image as color, texture, shape, ...
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Image Classification using SVM-RBF in the field of Image Processing
... in image capturing, storage, and internet technologies have made vast amounts of image data ...from image database. In recent years, image classification has become an interesting ...
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Novel image descriptors and learning methods for image classification applications
... Content-based image classification applications have expanded greatly due to the advent of an image era of big data resulting in the availability of large number of color images in the ...
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Context-aware Image-to-class Distances from Image Classification
... Saliency arises from the contrasts between the object and its neighbourhood. Inspired by the various saliency detection methods, we manage to divide the images into foreground and background. With the identified regions ...
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A Deep Learning Model for Image Classification
... Class image Classification, we created the dataset by crawling five different products such as Trees, Sunset, water, desert and ...The image data set consists of 2,000 natural scene images, where a ...
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Machine Learning framework for image classification
... Hereby in this paper, we are going to refer image classification. The main issue in image classification is features extraction and image vector representation. We expose the Bag of ...
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Super Characters: A Conversion from Sentiment Classification to Image Classification
... sentiment classification. This method converts the sentiment classification problem into image classification problem by project- ing texts into images and then applying CNN models for ...
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Texture Based Image Classification
... Texture classification is one of the four problem domains in the field of texture ...for classification is based on the segmentation procedure that is ...textured image classification issue ...
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Hyperspectral Image Classification
... (HS) image classification always suffers from varieties of artifacts, such as high dimensionality, limited or unbalanced training samples [7], spectral variability, and mixing ...supervised ...
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