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Accurate seed points classification using invariant moments & neural network
2015 Edition, May 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Segmentation is a key topic in computer vision and medical image processing. Furthermore, it is used in many medical applications and techniques such as registration. Currently, an accurate segmentation is still a challenging task. In this study, the segmentation process starts by...

Bacterial foraging optimization based Radial Basis Function Neural Network (BRBFNN) for identification and classification of plant leaf diseases: An automatic approach towards Plant Pathology
Volume PP - IEEE - Institute of Electrical and Electronics Engineers, Inc.

The contribution of a plant is highly important for both human life and environment. Plants do suffer from diseases, like human beings and animals. There is the number of plant diseases that occur and affects the normal growth of a plant. These diseases affect complete plant including leaf, stem,...

An Adaptive Region Growing Method using Similarity Set Score and Homogeneity Value based on Neutrosophic Set Domain for Ultrasound Image Segmentation
Volume PP - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Breast tumor segmentation in ultrasound is important for breast ultrasound (BUS) quantitative analysis and clinical diagnosis. Even this topic has been studied for a long time, it is still a challenging task to segment tumor in BUS accurately arising from difficulties of speckle noise and...

Random Walk Network for 3D Point Cloud Classification and Segmentation
2019 Edition, December 1, 2019 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Object classification and segmentation via point cloud are essential for mobile robot navigation and operation. A lot of researches ranging from 3D voxels, mesh gird and multi-view were proposed based on point cloud. However, an accurate point cloud classification is still a...

Invariant Information Clustering for Unsupervised Image Classification and Segmentation
2019 Edition, October 1, 2019 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We present a novel clustering objective that learns a neural network classifier from scratch, given only unlabelled data samples. The model discovers clusters that accurately match semantic classes, achieving state-of-the-art results in eight unsupervised clustering benchmarks...

Handwritten Signature Verification Using Image Invariants and Dynamic Features
2006 Edition, January 1, 2006 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this paper, a development of automatic signature classification system is proposed. We have presented offline and online signature verification system, based on the signature invariants and its dynamic features. The proposed system segments each signature based on its perceptually...

Robust aircraft classification using moment invariants, neural network, and split inversion learning
1991 Edition, Volume ii, January 1, 1991 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Summary form only given, as follows. A robust approach for classifying aircraft in the presence of noise was proposed and simulated. Preprocessing provides constant moment invariants for images in which the object is translated in position, rotated, or changed in scale. In the presence of...

Shape feature extraction from object corners
1994 Edition, January 1, 1994 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

A method to extract shape features based on corners is described. Corners contain most of the shape information. Extraction of shape features which are invariant to scaling, rotation and translation is an important problem in computer vision and automatic target recognition systems. A Canny...

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