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An investigation on local wrinkle-based extractor of age estimation
An investigation on local wrinkle-based extractor of age estimation

... layer (q) and one output layer (r). The total number of nodes in the input layer is determined according to the feature size, s, used for capturing input patterns. If the feature size, s, is 24 then the number of input layers will be set correspondingly. There are two hidden units. The number of out ...
Scalable spatial event representation
Scalable spatial event representation

... 2. VISUAL THESAURUS An image analysis framework requires a representation that allows fast data processing, meaningful data summarization, scalability with respect to dataset size and dimension, multi-feature representation, and efficient data understanding. Limited success towards this end has been ...
Comparison of Handwriting characters Accuracy using
Comparison of Handwriting characters Accuracy using

... of chain code techniques were compared. The results showed that the hotspot technique provides the largest average classification rates. Dayashankar Singh et al.[4] presented a new feature extraction technique to calculate only twelve directional feature inputs depending upon the gradients. Total 50 ...
- Sacramento - California State University
- Sacramento - California State University

... [10] to identify animals without disturbing them [4]. Photographic identification of individuals is an established technique [6], though underutilized because of the difficulties involved in making positive visual identification in large data sets [5]. In many cases, computer-aided identification of ...
A Committee of Neural Networks for Traffic Sign Classification
A Committee of Neural Networks for Traffic Sign Classification

... HE most successful hierarchical visual object recognition systems extract localized features from input images, convolving image patches with filters whose responses are then repeatedly sub-sampled and re-filtered, resulting in a deep feed-forward network architecture whose output feature vectors ar ...
IOSR Journal of Computer Engineering (IOSR-JCE)
IOSR Journal of Computer Engineering (IOSR-JCE)

... Character recognition process can be categorized in two types. One is Offline character recognition and another one is online character recognition. In offline character recognition system, document is first generated, digitized, stored in computer and then it is processed. While in case of online c ...
Unsupervised Object Counting without Object Recognition
Unsupervised Object Counting without Object Recognition

... a straightforward approach would be to perform explicit object detection [5], [7], [12]–[14]. Also, regression-based approaches have been proposed, which translate the image features into the number of objects with a regression model [8], [15], [16]. These approaches require labeled training data, w ...
Learning to Control Robotic Systems Presented at
Learning to Control Robotic Systems Presented at

Volumetric MRI Classification for Alzheimer`s Diseases Based on
Volumetric MRI Classification for Alzheimer`s Diseases Based on

... structures may be preferentially modified by particular cognitive skills, genes or diseases1,2. Morphological analysis of medical images is therefore used in a variety of research and clinical studies that detect and quantify spatially complex and often subtle abnormal imaging patterns of pathology. ...
An Effective Visual Descriptor Based on Color and - MEX
An Effective Visual Descriptor Based on Color and - MEX

... broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in ...
Leaf Vein Extraction Using Independent Component Analysis
Leaf Vein Extraction Using Independent Component Analysis

... conjugate of w(k), g can be any suitable non-linear contrast function, with derivative g’, and C is the covariance matrix of the mixtures, X. ...
SOILIE: A Computational Model of 2D Visual Imagination
SOILIE: A Computational Model of 2D Visual Imagination

... The Oracle of Objects uses a matrix of co-occurrence relations derived from Peekaboom‟s image content information. This matrix holds the frequencies at which two labels will appear in the same picture in the database. Taking the top n labels that co-occur with a particular query allows the module to ...
LeCun - NYU Computer Science
LeCun - NYU Computer Science

... Region Cov. Etc. ...
The Site-Model Construction Component of the RADIUS Testbed
The Site-Model Construction Component of the RADIUS Testbed

... The central component in the RADIUS modelsupported image exploitation paradigm, is the creation of a 3-dimensional model that captures the basic geometry of the site under examination. While many fully automated methods for site model construction show promising results, none are robust or general e ...
Compact color descriptor for fast image and video segment retrieval
Compact color descriptor for fast image and video segment retrieval

... resources. However for applications like content filtering, where the multimedia data and related descriptions are processed by a set-top box or a similar device with limited computational resource and limited bandwidth, it is imperative to use a compact representation. Even for a database applicati ...
An Application of Ant Colony Optimization to Image Clustering
An Application of Ant Colony Optimization to Image Clustering

... with unsupervised learning, commonly known as clustering, is to partition a given data set into groups (clusters) such that the data points in a cluster are more similar to each other than points in different clusters [1]. The clustering of images to semantic meaningful classes involves many image a ...
Image Pattern Recognition
Image Pattern Recognition

... Micrographs used in a Manual System D ...
pattern recognition - CIS @ Temple University
pattern recognition - CIS @ Temple University

... level quantization restricts these values to a finite range. Restricting the brightness values conserve storage; integers in the range 0 to 2^n require only n-bits to be represented. We would need only 4 bits per point for an image with brightness values in the range of 0 to 16 as oppose to 32 or 6 ...
Learning to Parse Images
Learning to Parse Images

... Neal [4] introduced generative models composed of multiple layers of stochastic logistic units connected in a directed acyclic graph. In general, as each unit has multiple parents, it is intractable to compute the posterior distribution over hidden variables when certain variables are observed. Howe ...
Pill-ID: Matching and Retrieval of Drug Pill Images
Pill-ID: Matching and Retrieval of Drug Pill Images

... circulated in our society. Identifying the source and manufacturer of these illicit drugs will help deter drug-related crimes. We have developed an automatic system, called Pill-ID to match drug pill images based on several features (i.e., imprint, color, and shape) of the tablet. The color and shap ...
Geometric Hashing
Geometric Hashing

... (5) Histogram all the hash table entries that received one or more votes. Determine those entries that received more than a certain number of votes -- each such entry corresponds to a potential match (hypothesis generation). (6) For each potential match, consider all the model-image feature pairs wh ...
various object recognition techniques for computer vision
various object recognition techniques for computer vision

... difficulty of modeling shapes generically and from the difficulty of abstracting reflections, textures, shadows and distortions caused by the image capture process. 5. APPEARANCE BASED OBJECT RECOGNITION Appearance-based object recognition systems are currently the most successful approach for deali ...
What is texture?
What is texture?

... Physical simulation • Advantages: – produce texture directly on 3D meshes, thus avoid texture mapping distortion problem ...
Debi Prasad Tripathy K. Guru Raghavendra Reddy
Debi Prasad Tripathy K. Guru Raghavendra Reddy

... increase  the  quality  of  the  ore.  The  vast  developments  in  the  area  of  artificial  intelligence  allows  fast   processing  of  full  color  digital images for the preferred  investigations.  In  this  paper,  a  novel   approach  to  categorize  the  ores   of  iron  feed  has  been  pr ...
Small Codes and Large Image Databases for Recognition
Small Codes and Large Image Databases for Recognition

... means we have a budget of very few bytes per image. – short binary codes allow very fast querying in standard hardware, either using hash tables or efficient bit-count operations ...
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Scale-invariant feature transform

Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving.The algorithm is patented in the US; the owner is the University of British Columbia.
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