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Research paper thumbnail of Image Augmentation Techniques for Mammogram Analysis

Journal of Imaging

Research in the medical imaging field using deep learning approaches has become progressively con... more Research in the medical imaging field using deep learning approaches has become progressively contingent. Scientific findings reveal that supervised deep learning methods’ performance heavily depends on training set size, which expert radiologists must manually annotate. The latter is quite a tiring and time-consuming task. Therefore, most of the freely accessible biomedical image datasets are small-sized. Furthermore, it is challenging to have big-sized medical image datasets due to privacy and legal issues. Consequently, not a small number of supervised deep learning models are prone to overfitting and cannot produce generalized output. One of the most popular methods to mitigate the issue above goes under the name of data augmentation. This technique helps increase training set size by utilizing various transformations and has been publicized to improve the model performance when tested on new data. This article surveyed different data augmentation techniques employed on mammogra...

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Research paper thumbnail of Sign and Human Action Detection Using Deep Learning

Journal of Imaging

Human beings usually rely on communication to express their feeling and ideas and to solve disput... more Human beings usually rely on communication to express their feeling and ideas and to solve disputes among themselves. A major component required for effective communication is language. Language can occur in different forms, including written symbols, gestures, and vocalizations. It is usually essential for all of the communicating parties to be fully conversant with a common language. However, to date this has not been the case between speech-impaired people who use sign language and people who use spoken languages. A number of different studies have pointed out a significant gaps between these two groups which can limit the ease of communication. Therefore, this study aims to develop an efficient deep learning model that can be used to predict British sign language in an attempt to narrow this communication gap between speech-impaired and non-speech-impaired people in the community. Two models were developed in this research, CNN and LSTM, and their performance was evaluated using...

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Research paper thumbnail of A Low Cost Solution for NOAA Remote Sensing

Proceedings of the 7th International Conference on Sensor Networks, 2018

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Research paper thumbnail of Video Object Recognition and Modeling by SIFT Matching Optimization

Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods, 2014

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Research paper thumbnail of Meso-scale topological cues influence extracellular matrix production in a large deformation, elastomeric scaffold model

Soft Matter, 2018

Fiber intersection density affects meso-scale cell aspect ratio and extracellular matrix synthesi... more Fiber intersection density affects meso-scale cell aspect ratio and extracellular matrix synthesis in an elastomeric scaffold model under organ-scale deformation.

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Research paper thumbnail of SATSal: A Multi-Level Self-Attention Based Architecture for Visual Saliency Prediction

IEEE Access, 2022

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Research paper thumbnail of A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

IEEE Access, 2020

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Research paper thumbnail of Saliency Map for Visual Perception

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Research paper thumbnail of Automatic Multi-seed Detection for MR Breast Image Segmentation

Image Analysis and Processing - ICIAP 2017, 2017

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Research paper thumbnail of Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

Image Analysis and Processing - ICIAP 2017, 2017

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Research paper thumbnail of Image Content Enhancement Through Salient Regions Segmentation for People With Color Vision Deficiencies

i-Perception, 2019

Color vision deficiencies affect visual perception of colors and, more generally, color images. S... more Color vision deficiencies affect visual perception of colors and, more generally, color images. Several sciences such as genetics, biology, medicine, and computer vision are involved in studying and analyzing vision deficiencies. As we know from visual saliency findings, human visual system tends to fix some specific points and regions of the image in the first seconds of observation summing up the most important and meaningful parts of the scene. In this article, we provide some studies about human visual system behavior differences between normal and color vision-deficient visual systems. We eye-tracked the human fixations in first 3 seconds of observation of color images to build real fixation point maps. One of our contributions is to detect the main differences between the aforementioned human visual systems related to color vision deficiencies by analyzing real fixation maps among people with and without color vision deficiencies. Another contribution is to provide a method to...

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Research paper thumbnail of Views selection for SIFT based object modeling and recognition

2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2016

In this paper we focus on automatically learning object models in the framework of keypoint based... more In this paper we focus on automatically learning object models in the framework of keypoint based object recognition. The proposed method uses a collection of views of the objects to build the model. For each object the collection is composed of N×M views obtained rotating the object around its vertical and horizontal axis. As keypoint based object recognition using a complete set of views is computationally expensive, we focused on the definition of a selection method that creates, for each object, a subset of the initial views that visually summarize the characteristics of the object and should be suited for recognition. We select the views by determining maxima and minima of a function, based on the number of SIFT descriptors able to evaluate views similarity and relevance. Experimental results for recognition on a publicly available dataset are reported.

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Research paper thumbnail of Why You Trust in Visual Saliency

Lecture Notes in Computer Science, 2015

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Research paper thumbnail of Copy–Move Forgery Detection by Matching Triangles of Keypoints

IEEE Transactions on Information Forensics and Security, 2015

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Research paper thumbnail of An Unsupervised Method for Suspicious Regions Detection in Mammogram Images

Proceedings of the International Conference on Pattern Recognition Applications and Methods, 2015

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Research paper thumbnail of Object Recognition and Modeling Using SIFT Features

Lecture Notes in Computer Science, 2013

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Research paper thumbnail of Detecting multiple copies in tampered images

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Research paper thumbnail of Copy-move forgery detection via texture description

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Research paper thumbnail of Visual saliency by keypoints distribution analysis

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Research paper thumbnail of Saliency based image cropping

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Research paper thumbnail of Image Augmentation Techniques for Mammogram Analysis

Journal of Imaging

Research in the medical imaging field using deep learning approaches has become progressively con... more Research in the medical imaging field using deep learning approaches has become progressively contingent. Scientific findings reveal that supervised deep learning methods’ performance heavily depends on training set size, which expert radiologists must manually annotate. The latter is quite a tiring and time-consuming task. Therefore, most of the freely accessible biomedical image datasets are small-sized. Furthermore, it is challenging to have big-sized medical image datasets due to privacy and legal issues. Consequently, not a small number of supervised deep learning models are prone to overfitting and cannot produce generalized output. One of the most popular methods to mitigate the issue above goes under the name of data augmentation. This technique helps increase training set size by utilizing various transformations and has been publicized to improve the model performance when tested on new data. This article surveyed different data augmentation techniques employed on mammogra...

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Research paper thumbnail of Sign and Human Action Detection Using Deep Learning

Journal of Imaging

Human beings usually rely on communication to express their feeling and ideas and to solve disput... more Human beings usually rely on communication to express their feeling and ideas and to solve disputes among themselves. A major component required for effective communication is language. Language can occur in different forms, including written symbols, gestures, and vocalizations. It is usually essential for all of the communicating parties to be fully conversant with a common language. However, to date this has not been the case between speech-impaired people who use sign language and people who use spoken languages. A number of different studies have pointed out a significant gaps between these two groups which can limit the ease of communication. Therefore, this study aims to develop an efficient deep learning model that can be used to predict British sign language in an attempt to narrow this communication gap between speech-impaired and non-speech-impaired people in the community. Two models were developed in this research, CNN and LSTM, and their performance was evaluated using...

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Research paper thumbnail of A Low Cost Solution for NOAA Remote Sensing

Proceedings of the 7th International Conference on Sensor Networks, 2018

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Research paper thumbnail of Video Object Recognition and Modeling by SIFT Matching Optimization

Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods, 2014

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Research paper thumbnail of Meso-scale topological cues influence extracellular matrix production in a large deformation, elastomeric scaffold model

Soft Matter, 2018

Fiber intersection density affects meso-scale cell aspect ratio and extracellular matrix synthesi... more Fiber intersection density affects meso-scale cell aspect ratio and extracellular matrix synthesis in an elastomeric scaffold model under organ-scale deformation.

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Research paper thumbnail of SATSal: A Multi-Level Self-Attention Based Architecture for Visual Saliency Prediction

IEEE Access, 2022

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Research paper thumbnail of A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

IEEE Access, 2020

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Research paper thumbnail of Saliency Map for Visual Perception

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Automatic Multi-seed Detection for MR Breast Image Segmentation

Image Analysis and Processing - ICIAP 2017, 2017

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Research paper thumbnail of Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

Image Analysis and Processing - ICIAP 2017, 2017

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Image Content Enhancement Through Salient Regions Segmentation for People With Color Vision Deficiencies

i-Perception, 2019

Color vision deficiencies affect visual perception of colors and, more generally, color images. S... more Color vision deficiencies affect visual perception of colors and, more generally, color images. Several sciences such as genetics, biology, medicine, and computer vision are involved in studying and analyzing vision deficiencies. As we know from visual saliency findings, human visual system tends to fix some specific points and regions of the image in the first seconds of observation summing up the most important and meaningful parts of the scene. In this article, we provide some studies about human visual system behavior differences between normal and color vision-deficient visual systems. We eye-tracked the human fixations in first 3 seconds of observation of color images to build real fixation point maps. One of our contributions is to detect the main differences between the aforementioned human visual systems related to color vision deficiencies by analyzing real fixation maps among people with and without color vision deficiencies. Another contribution is to provide a method to...

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Research paper thumbnail of Views selection for SIFT based object modeling and recognition

2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2016

In this paper we focus on automatically learning object models in the framework of keypoint based... more In this paper we focus on automatically learning object models in the framework of keypoint based object recognition. The proposed method uses a collection of views of the objects to build the model. For each object the collection is composed of N×M views obtained rotating the object around its vertical and horizontal axis. As keypoint based object recognition using a complete set of views is computationally expensive, we focused on the definition of a selection method that creates, for each object, a subset of the initial views that visually summarize the characteristics of the object and should be suited for recognition. We select the views by determining maxima and minima of a function, based on the number of SIFT descriptors able to evaluate views similarity and relevance. Experimental results for recognition on a publicly available dataset are reported.

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Research paper thumbnail of Why You Trust in Visual Saliency

Lecture Notes in Computer Science, 2015

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Research paper thumbnail of Copy–Move Forgery Detection by Matching Triangles of Keypoints

IEEE Transactions on Information Forensics and Security, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of An Unsupervised Method for Suspicious Regions Detection in Mammogram Images

Proceedings of the International Conference on Pattern Recognition Applications and Methods, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Object Recognition and Modeling Using SIFT Features

Lecture Notes in Computer Science, 2013

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Research paper thumbnail of Detecting multiple copies in tampered images

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Copy-move forgery detection via texture description

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Visual saliency by keypoints distribution analysis

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Saliency based image cropping

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