Image analysis is used as a fundamental tool for recognizing, differentiating, and. quantifying diverse types of images, including grayscale and color images, multi-. spectral images for a few ...
Medical image analysis using deep learning algorithms
The primary aims of the research are to identify, assess, and differentiate all key papers within the realm of using DL methods medical image analysis. A systematic literature review (SLR) can be utilized to scrutinize the constituents and characteristics of methods for accomplishing the aforementioned objectives.
Deep learning models for digital image processing: a review
Within the domain of image processing, a wide array of methodologies is dedicated to tasks including denoising, enhancement, segmentation, feature extraction, and classification. These techniques collectively address the challenges and opportunities posed by different aspects of image analysis and manipulation, enabling applications across various fields. Each of these methodologies ...
Medical image analysis based on deep learning approach
Deep Learning Approach (DLA) in medical image analysis emerges as a fast-growing research field. DLA has been widely used in medical imaging to detect the presence or absence of the disease. This paper presents the development of artificial neural networks, comprehensive analysis of DLA, which delivers promising medical imaging applications.
A Review Paper about Deep Learning for Medical Image Analysis
In this study, we summarize the current developments in deep learning approaches for medical image analysis. The paper is organized as follows: first, survey papers related to medical image analysis are discussed in Section 2. Then, in Section 3, CNN models employed in the radiology field and approaches for improving CNN performance are described.
The ImageJ ecosystem: Open‐source software for image visualization
While ImageJ is a useful image analysis tool for research in the life sciences, it also serves a broader audience as a basic image viewer and annotation tool. ... Krull A, Buchholz T‐O, Jug F. Noise2Void ‐ learning denoising from single noisy images. Paper presented at: Conference on Computer Vision and Pattern Recognition (CVPR); 2019; pp ...
Images Research Guide: Image Analysis
It is important to analyze and evaluate images you use for research, study, and presentations. Images should be analyzed and evaluated like any other source, such as journal articles or books, to determine their quality, reliability, and appropriateness. Images should be analyzed evaluated on several levels. Visual analysis is an important step ...
Advances in Deep Learning-Based Medical Image Analysis
Although there exist a number of reviews on deep learning methods on medical image analysis [4-13], most of them emphasize either on general deep learning techniques or on specific clinical applications.The most comprehensive review paper is the work of Litjens et al. published in 2017 [].Deep learning is such a quickly evolving research field; numerous state-of-the-art works have been ...
Medical image analysis based on deep learning approach
This paper discusses the new algorithms and strategies in the area of deep learning. In this brief introduction to DLA in medical image analysis, there are two objectives. The first one is an introduction to the field of deep learning and the associated theory. The second is to provide a general overview of the medical image analysis using DLA.
Medical Image Analysis for Detection, Treatment and Planning of Disease
Medical Image Analysis (MIA) is a field of study that deals with the processing, analysis, and interpretation of the medical images for diagnosis, treatment planning, and research. It involves the application of various techniques and algorithms to extract meaningful information from medical images, e.g. X-
Applications in Image Analysis and Pattern Recognition
Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications. ... Image analysis and pattern ...
Image Analysis in Autonomous Vehicles: A Review of the Latest AI ...
The integration of advanced image analysis using artificial intelligence (AI) is pivotal for the evolution of autonomous vehicles (AVs). This article provides a thorough review of the most significant datasets and latest state-of-the-art AI solutions employed in image analysis for AVs. Datasets such as Cityscapes, NuScenes, CARLA, and Talk2Car form the benchmarks for training and evaluating ...
An Analysis Of Convolutional Neural Networks For Image Classification
Abstract. This paper presents an empirical analysis of theperformance of popular convolutional neural networks (CNNs) for identifying objects in real time video feeds. The most popular convolution neural networks for object detection and object category classification from images are Alex Nets, GoogLeNet, and ResNet50.
Comparative analysis of deep learning image detection algorithms
A computer views all kinds of visual media as an array of numerical values. As a consequence of this approach, they require image processing algorithms to inspect contents of images. This project compares 3 major image processing algorithms: Single Shot Detection (SSD), Faster Region based Convolutional Neural Networks (Faster R-CNN), and You Only Look Once (YOLO) to find the fastest and most ...
MRI image analysis methods and applications: an algorithmic perspective
The level set family of algorithms originated from the research conducted by Sethian and coworkers, who developed an algorithm that can automatically track curves in any dimension. 21 The level set methodologies have been applied to other fields, including medical image analysis, and form the basis of a family of segmentation algorithms. The ...
A Survey of Medical Image Analysis Using Deep Learning Approaches
With the expanding development of Deep Learning techniques Medical Image Analysis have become an active field of research. Medical Image Analysis typically refers to the utilization of various kinds of image modalities and techniques to obtain images of the human body which in turn can be used by medical experts for diagnosis along with treatment of patients. This paper provides a survey of ...
Visual media analysis for Instagram and other online platforms
Abstract. Instagram is currently the social media platform most associated with online images (and their analysis), but images from other platforms also can be collected and grouped, arrayed by similarity, stacked, matched, stained, labelled, depicted as network, placed side by side and otherwise analytically displayed.
Visual Methodologies in Qualitative Research: Autophotography and Photo
Visual methodologies are used to understand and interpret images (Barbour, 2014) and include photography, film, video, painting, drawing, collage, sculpture, artwork, graffiti, advertising, and cartoons.Visual methodologies are a new and novel approach to qualitative research derived from traditional ethnography methods used in anthropology and sociology.
Image Segmentation and its Different Techniques: An In-Depth Analysis
Image segmentation is the most important part of image processing, separating an image into multiple meaningful parts. In this area of the image segmentation, new technologies emerge day after day. In this paper, an in-depth analysis is carried out on some frequently adopted image segmentation techniques such as thresholding based techniques, edge detection based or boundary based techniques ...
Techniques and Challenges of Image Segmentation: A Review
Image segmentation, which has become a research hotspot in the field of image processing and computer vision, refers to the process of dividing an image into meaningful and non-overlapping regions, and it is an essential step in natural scene understanding. Despite decades of effort and many achievements, there are still challenges in feature extraction and model design. In this paper, we ...
Progress on image analytics: Implications for tourism and hospitality
This paper offers the progress of image definitions, features and related theories, as well as presents a methodological framework for conducting image-related studies, complementing the dominant textual analysis used in tourism and hospitality research. The paper makes contributions to the tourism methodological literature by developing a ...
A review of the studies on social media images from the perspective of
In this paper, the research progress of images in social media is summarized by comprehensive induction. Through the extraction and analysis of relevant literature and key words, this paper reveals the research hotspots and development trends of visual information interaction in image social interaction.
Texts and Images as Data in Qualitative Social Research: Proposing a
In order to continue this methodological debate in a constructive manner, it is necessary to make a pivotal, but to my knowledge often neglected distinction: The distinction between texts and images as historical or contemporary primary research data in the study of cultures and societies on the one hand, and "text" and "image" as theoretical concepts and epistemological metaphors on ...
Creating clear and informative image-based figures for scientific
Image analysis. First, we confirmed that images are common in the 3 biology subfields analyzed. More than half of the original research articles in the sample contained images (plant science: 68%, cell biology: 72%, physiology: 55%). Among the 580 papers that included images, microscope images were very common in all 3 fields (61% to 88%, Fig ...
Shear Wave Elastography‐Assisted Ultrasound Breast Image Analysis and
In this paper, shear wave elastography was used to study and analyze the images of the breast in-depth and identify the abnormal image data. ... Research Article. Open Access. Shear Wave Elastography-Assisted Ultrasound Breast Image Analysis and Identification of Abnormal Data. Caoxin Yan, Corresponding Author. Caoxin Yan [email protected ...
New tools use AI 'fingerprints' to detect altered photos, videos
New research led by Binghamton University breaks down images using frequency domain analysis techniques and looks for anomalies that could indicate they are generated by AI. ... The research paper also explores ways that GANIA could be used to identify a photo's AI origins, which limits misinformation spread through deepfake images. ...
GPT-fabricated scientific papers on Google Scholar: Key features
Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research.
A novel color image encryption method based on new three ...
In recent years, the field of information science has seen a surge in research focused on digital image security. Chaotic systems have emerged as essential tools in the development of image encryption algorithms due to their unpredictability and sensitivity to initial values. In this paper, a novel three-dimensional chaotic system is proposed and its chaotic behavior is validated through an ...
High-Dimensional Yield Analysis Using Sparse ...
DOI: 10.1145/3670474.3685954 Corpus ID: 272381053; High-Dimensional Yield Analysis Using Sparse Representation for Long-Tailed Distribution @article{Wang2024HighDimensionalYA, title={High-Dimensional Yield Analysis Using Sparse Representation for Long-Tailed Distribution}, author={Ziqi Wang and Weihan Sun and Zhongxi Guo and Xiao Shi and Long Bao Shi}, journal={Proceedings of the 2024 ACM/IEEE ...
Do Price Deflators for High-Tech Goods Overstate Quality Change?
This paper studies chained price indexes for goods in high-tech sectors, how they handle quality change and whether they will likely suffer from chain drift issues. We argue that chained indexes do not handle quality change properly; though the underlying bilateral indexes hold quality constant just fine, the chained index does not, a problem we call comingling.
COMMENTS
Image analysis is used as a fundamental tool for recognizing, differentiating, and. quantifying diverse types of images, including grayscale and color images, multi-. spectral images for a few ...
The primary aims of the research are to identify, assess, and differentiate all key papers within the realm of using DL methods medical image analysis. A systematic literature review (SLR) can be utilized to scrutinize the constituents and characteristics of methods for accomplishing the aforementioned objectives.
Within the domain of image processing, a wide array of methodologies is dedicated to tasks including denoising, enhancement, segmentation, feature extraction, and classification. These techniques collectively address the challenges and opportunities posed by different aspects of image analysis and manipulation, enabling applications across various fields. Each of these methodologies ...
Deep Learning Approach (DLA) in medical image analysis emerges as a fast-growing research field. DLA has been widely used in medical imaging to detect the presence or absence of the disease. This paper presents the development of artificial neural networks, comprehensive analysis of DLA, which delivers promising medical imaging applications.
In this study, we summarize the current developments in deep learning approaches for medical image analysis. The paper is organized as follows: first, survey papers related to medical image analysis are discussed in Section 2. Then, in Section 3, CNN models employed in the radiology field and approaches for improving CNN performance are described.
While ImageJ is a useful image analysis tool for research in the life sciences, it also serves a broader audience as a basic image viewer and annotation tool. ... Krull A, Buchholz T‐O, Jug F. Noise2Void ‐ learning denoising from single noisy images. Paper presented at: Conference on Computer Vision and Pattern Recognition (CVPR); 2019; pp ...
It is important to analyze and evaluate images you use for research, study, and presentations. Images should be analyzed and evaluated like any other source, such as journal articles or books, to determine their quality, reliability, and appropriateness. Images should be analyzed evaluated on several levels. Visual analysis is an important step ...
Although there exist a number of reviews on deep learning methods on medical image analysis [4-13], most of them emphasize either on general deep learning techniques or on specific clinical applications.The most comprehensive review paper is the work of Litjens et al. published in 2017 [].Deep learning is such a quickly evolving research field; numerous state-of-the-art works have been ...
This paper discusses the new algorithms and strategies in the area of deep learning. In this brief introduction to DLA in medical image analysis, there are two objectives. The first one is an introduction to the field of deep learning and the associated theory. The second is to provide a general overview of the medical image analysis using DLA.
Medical Image Analysis (MIA) is a field of study that deals with the processing, analysis, and interpretation of the medical images for diagnosis, treatment planning, and research. It involves the application of various techniques and algorithms to extract meaningful information from medical images, e.g. X-
Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications. ... Image analysis and pattern ...
The integration of advanced image analysis using artificial intelligence (AI) is pivotal for the evolution of autonomous vehicles (AVs). This article provides a thorough review of the most significant datasets and latest state-of-the-art AI solutions employed in image analysis for AVs. Datasets such as Cityscapes, NuScenes, CARLA, and Talk2Car form the benchmarks for training and evaluating ...
Abstract. This paper presents an empirical analysis of theperformance of popular convolutional neural networks (CNNs) for identifying objects in real time video feeds. The most popular convolution neural networks for object detection and object category classification from images are Alex Nets, GoogLeNet, and ResNet50.
A computer views all kinds of visual media as an array of numerical values. As a consequence of this approach, they require image processing algorithms to inspect contents of images. This project compares 3 major image processing algorithms: Single Shot Detection (SSD), Faster Region based Convolutional Neural Networks (Faster R-CNN), and You Only Look Once (YOLO) to find the fastest and most ...
The level set family of algorithms originated from the research conducted by Sethian and coworkers, who developed an algorithm that can automatically track curves in any dimension. 21 The level set methodologies have been applied to other fields, including medical image analysis, and form the basis of a family of segmentation algorithms. The ...
With the expanding development of Deep Learning techniques Medical Image Analysis have become an active field of research. Medical Image Analysis typically refers to the utilization of various kinds of image modalities and techniques to obtain images of the human body which in turn can be used by medical experts for diagnosis along with treatment of patients. This paper provides a survey of ...
Abstract. Instagram is currently the social media platform most associated with online images (and their analysis), but images from other platforms also can be collected and grouped, arrayed by similarity, stacked, matched, stained, labelled, depicted as network, placed side by side and otherwise analytically displayed.
Visual methodologies are used to understand and interpret images (Barbour, 2014) and include photography, film, video, painting, drawing, collage, sculpture, artwork, graffiti, advertising, and cartoons.Visual methodologies are a new and novel approach to qualitative research derived from traditional ethnography methods used in anthropology and sociology.
Image segmentation is the most important part of image processing, separating an image into multiple meaningful parts. In this area of the image segmentation, new technologies emerge day after day. In this paper, an in-depth analysis is carried out on some frequently adopted image segmentation techniques such as thresholding based techniques, edge detection based or boundary based techniques ...
Image segmentation, which has become a research hotspot in the field of image processing and computer vision, refers to the process of dividing an image into meaningful and non-overlapping regions, and it is an essential step in natural scene understanding. Despite decades of effort and many achievements, there are still challenges in feature extraction and model design. In this paper, we ...
This paper offers the progress of image definitions, features and related theories, as well as presents a methodological framework for conducting image-related studies, complementing the dominant textual analysis used in tourism and hospitality research. The paper makes contributions to the tourism methodological literature by developing a ...
In this paper, the research progress of images in social media is summarized by comprehensive induction. Through the extraction and analysis of relevant literature and key words, this paper reveals the research hotspots and development trends of visual information interaction in image social interaction.
In order to continue this methodological debate in a constructive manner, it is necessary to make a pivotal, but to my knowledge often neglected distinction: The distinction between texts and images as historical or contemporary primary research data in the study of cultures and societies on the one hand, and "text" and "image" as theoretical concepts and epistemological metaphors on ...
Image analysis. First, we confirmed that images are common in the 3 biology subfields analyzed. More than half of the original research articles in the sample contained images (plant science: 68%, cell biology: 72%, physiology: 55%). Among the 580 papers that included images, microscope images were very common in all 3 fields (61% to 88%, Fig ...
In this paper, shear wave elastography was used to study and analyze the images of the breast in-depth and identify the abnormal image data. ... Research Article. Open Access. Shear Wave Elastography-Assisted Ultrasound Breast Image Analysis and Identification of Abnormal Data. Caoxin Yan, Corresponding Author. Caoxin Yan [email protected ...
New research led by Binghamton University breaks down images using frequency domain analysis techniques and looks for anomalies that could indicate they are generated by AI. ... The research paper also explores ways that GANIA could be used to identify a photo's AI origins, which limits misinformation spread through deepfake images. ...
Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research.
In recent years, the field of information science has seen a surge in research focused on digital image security. Chaotic systems have emerged as essential tools in the development of image encryption algorithms due to their unpredictability and sensitivity to initial values. In this paper, a novel three-dimensional chaotic system is proposed and its chaotic behavior is validated through an ...
DOI: 10.1145/3670474.3685954 Corpus ID: 272381053; High-Dimensional Yield Analysis Using Sparse Representation for Long-Tailed Distribution @article{Wang2024HighDimensionalYA, title={High-Dimensional Yield Analysis Using Sparse Representation for Long-Tailed Distribution}, author={Ziqi Wang and Weihan Sun and Zhongxi Guo and Xiao Shi and Long Bao Shi}, journal={Proceedings of the 2024 ACM/IEEE ...
This paper studies chained price indexes for goods in high-tech sectors, how they handle quality change and whether they will likely suffer from chain drift issues. We argue that chained indexes do not handle quality change properly; though the underlying bilateral indexes hold quality constant just fine, the chained index does not, a problem we call comingling.