In this paper, results of an experimental study of a deep convolution neural network architecture which can classify different handwritten digits using EBLearn library [1] are reported. The purpose of this neural network is to classify input images into 10 different classes or digits (0-9) and to explore new findings. The input dataset used consists of digits images of size 32X32 in grayscale (...

We build a dataset including four kinds of multispectral images with labeled key point correspondence. The dataset includes 7 RGB/NIR image pairs, 4 RGB/Depth image pairs, 3 Flash/no-flash image pairs and 4 different exposure image pairs. In each pair, we uniformly select corner points and label their correspondences. The resolution of the RGB/Depth image pairs is 640 × 480 and all the other im...

We present BreakingNews, a novel dataset with approximately 100K news articles including images, text and captions, and enriched with heterogeneous meta-data (e.g. GPS coordinates and popularity metrics). The tenuous connection between the images and text in news data is appropriate to take work at the intersection of Computer Vision and Natural Language Processing to the next step, hence we ho...

A database of images of approximately 960 unique plants belonging to 12 species at several growth stages is made publicly available. It comprises annotated RGB images with a physical resolution of roughly 10 pixels per mm. To standardise the evaluation of classification results obtained with the database, a benchmark based on f1 scores is proposed. The dataset is available at https: // vision. ...

In this article, we propose a new method for localizing optic disc in retinal images. Localizing the optic disc and its center is the first step of most vessel segmentation, disease diagnostic, and retinal recognition algorithms. We use optic disc of the first four retinal images in DRIVE dataset to extract the histograms of each color component. Then, we calculate the average of histograms for...

We apply computer vision methods to the task of automatically predicting human attractiveness from frontal face images. A dataset of thousands of images and corresponding scores was obtained from a popular website that asks viewers to rate the attractiveness of the people appearing in the images. We applied several kernel regression techniques to the problem and found that while all techniques ...

We describe the acquisition of a large, diverse set of rebroadcast images captured by a screen-grab, scanning a printed photo, or rephotographing a displayed or a printed photo. This dataset consists of 14, 500 rebroadcast images captured from a diverse set of devices: 234 displays, 173 scanners, 282 printers, and 180 recapture cameras. The diversity of this dataset—across devices and types of ...

This Paper aims at classification of flower images by means of Gist descriptor and statistical features using SVM classifier. With advances in digital image processing, automated classification of flower images over large categories of dataset is possible by knowing the name of the flower. In case of unknown species name, classification of flower image can be performed by its visual content. Th...