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Embedding neural networks for semantic association in content based image retrieval
TLDR
In this paper a Neural Network based architecture for content based image retrieval is presented which is based on the concept of in-depth texture analysis of images. Expand
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Content Based Image Retrieval Using Embedded Neural Networks with Bandletized Regions
TLDR
A bandelet transform based image representation technique is presented in this paper, which reliably returns the information about the major objects found in an image. Expand
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Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images
Due to the powerful image editing tools images are open to several manipulations; therefore, their authenticity is becoming questionable especially when images have influential power, for example, inExpand
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Fall detection through acoustic Local Ternary Patterns
TLDR
We propose a framework that detects falls by using acoustic Local Ternary Patterns (acoustic-LTPs) by analyzing environmental sounds. Expand
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Categorical image retrieval through genetically optimized support vector machines (GOSVM) and hybrid texture features
TLDR
We have combined genetic algorithm and support vector machines to reduce the existing gap between high-level semantic content of the images and the information provided by their low-level descriptors. Expand
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Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines
TLDR
We proposed a novel technique to precisely detect the various stages of the diabetic retinopathy by extending the research of the content-based image retrieval domain. Expand
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Melanoma lesion detection and segmentation using deep region based convolutional neural network and fuzzy C-means clustering
TLDR
A deep region based convolutional neural network (RCNN) is proposed for automated Melanoma region segmentation using dermoscopic images to overcome the challenges of automatedMelanoma segmentation within dermatological images. Expand
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Robust Human Activity Recognition Using Multimodal Feature-Level Fusion
TLDR
This paper presents a viable multimodal feature-level fusion approach for robust human action recognition, which utilizes data from multiple sensors, including RGB camera, depth sensor, and wearable inertial sensors. Expand
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Copy-move forgery detection through stationary wavelets and local binary pattern variance for forensic analysis in digital images.
TLDR
The most common image tampering often for malicious purposes is to copy a region of the same image and paste to hide some other region. Expand
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A framework for fall detection of elderly people by analyzing environmental sounds through acoustic local ternary patterns
TLDR
The elderly people living alone or life of a patient face distress situations particularly in case of falling and becoming unable to ask for help. Expand
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