Acute Lymphoblastic Leukemia (ALL) is caused due to increase in number of abnormal lymphocyte cells in blood or bone marrow. This paper presents a methodology for automatic detection of the abnormal lymphocytes in a g...
详细信息
ISBN:
(纸本)9781479923618
Acute Lymphoblastic Leukemia (ALL) is caused due to increase in number of abnormal lymphocyte cells in blood or bone marrow. This paper presents a methodology for automatic detection of the abnormal lymphocytes in a given image of the blood sample. We have used local binary pattern (LBP) features for classifying the lymphocyte cell as blast or normal. LBP texture features of blood nucleus are investigated for the detection of ALL. We have also used shape features for classification and a comparative analysis of both the features is performed. It is seen that the LBP features provide reasonably good accuracy in classification.
local binary pattern is a descriptor whose purpose is to summarize the local structure of the images. The goal is to be able to discriminate different images. This method has gone through a large number of changes and...
详细信息
Deep learning is well known as a method to extract hierarchical representations of data. In this paper a novel unsupervised deep learning based methodology, named local binary pattern Network (LBPNet), is proposed to ...
详细信息
ISBN:
(纸本)9781467399616
Deep learning is well known as a method to extract hierarchical representations of data. In this paper a novel unsupervised deep learning based methodology, named local binary pattern Network (LBPNet), is proposed to efficiently extract and compare high-level over-complete features in multilayer hierarchy. The LBPNet retains the same topology of Convolutional Neural Network (CNN) - one of the most well studied deep learning architectures - whereas the trainable kernels are replaced by the off-the-shelf computer vision descriptor (i.e., LBP). This enables the LBPNet to achieve a high recognition accuracy without requiring any costly model learning approach on massive data. Through extensive numerical experiments using the public benchmarks (i.e., FERET and LFW), LBPNet has shown that it is comparable to other unsupervised methods.
Advancements in medical science have led to new approaches for preventing, diagnosing, and treating brain tumors, studied by researchers across different fields. The accurate identification of tumors in MRI scans can ...
详细信息
ISBN:
(纸本)9783031451690;9783031451706
Advancements in medical science have led to new approaches for preventing, diagnosing, and treating brain tumors, studied by researchers across different fields. The accurate identification of tumors in MRI scans can assist in disease identification, treatment evaluation, and radiation-based therapies. Currently, humans manually perform this task, but research has explored the integration of computer processing in MRI analysis. While MRIs provide a comprehensive view of the brain to identify tumors, they lack accuracy in pinpointing their location and size. To address this, an improved version of local binary pattern (LBP) encoded optimized Convolutional neural network is proposed to improve diagnostic accuracy. LBP captures texture information in a local neighborhood of each pixel, providing additional features to learn from and enhancing the accuracy of texture-based image classification. The model is evaluated on the Figshare dataset through multiple experiments.
We present a method of robustly identifying a text block in complex web images. The method is a MLP (Multilayer perceptron) classifier trained on LBP (local binary patterns), wavelet and shape feature spaces. Especial...
详细信息
Computer assistance has the potential for increasing safety and accuracy during retinal laser treatment using the slit-lamp. In this context, intra-operative retinal mapping is a fundamental requirement to overlay rel...
详细信息
Scale-invariant feature transform (SIFT) is a feature point based method using the orientation descriptor for pattern recognition. It is robust under the variation of scale and rotation changes, but the computation co...
详细信息
This paper deals with automatic face recognition in the context of a real application for person identification developed for the Czech News Agency (TK). We focus on popular local binary patterns (LPBs) that are frequ...
详细信息
This study aims to improve the accuracy of coffee bean classification by utilizing local binary pattern (LBP) extraction with Modular Neural Network (MNN). Coffee, one of Indonesia's leading commodities, plays a v...
详细信息
local binary patterns and Census share similar ideas of encoding the local region by establishing the relationship between neighbor pixels to obtain robust feature transformation. Recently, LBP and its variants have b...
详细信息
暂无评论