Intelligent Systems Reference Library
Volume 1 / 2009 to Volume 256 / 2024
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Article
A Study on the Validity and Scope of Self-Similarity Property in Super-Resolution of Medical Images
Super-resolution is an ill-posed inverse problem. It needs a self-similarity regularization term in its formulation to solve the issue. Researchers have studied self-similarity in natural images thoroughly and...
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Book Series
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Chapter
Mitigating Domain Shift in Logo Detection: An Adversarial Learning-Based Approach
This chapter discusses a domain adaptation-based technique aimed at mitigating the domain-shift challenge in logo detection. In real-world applications, we face a domain shift problem between the training data...
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Chapter
Introduction to Logo Detection
This chapter discusses logo detection, highlighting its significant applications and the primary challenges it faces. Logo detection is pivotal in various fields such as market tracking, product growth analysi...
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Chapter
Deep Convolutional Neural Networks
Over the last decade, deep learning frameworks have revolutionized the field of computer vision, delivering state-of-the-art performance across various applications. The advent of deep convolutional neural net...
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Chapter
Weakly Supervised Logo Detection Approach
The previous chapters discuss Deep Learning-based feature extractor frameworks and challenges related to detection tasks, with a specific focus on logo recognition. Most existing logo detection methods often r...
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Book
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Chapter
Anchorfree Logo Detection Framework
This chapter discusses attention mechanism-based anchorfree logo detection framework and lightweight CNNs modules. To perform precise and efficient logo detection, we propose a framework, LogoNet, which consis...
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Chapter
Unsupervised Logo Detection with Adversarial Domain Adaptation from Synthetic to Real Images
In this chapter, we address the challenges posed by limited training data and domain shift in the field of logo detection. Recent advancements have illustrated the effectiveness of convolutional neural network...
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Article
Open AccessThe effect of sequential combination of mirror therapy and robot-assisted therapy on motor function, daily function, and self-efficacy after stroke
Robot-assisted therapy and mirror therapy are both effective in promoting upper limb function after stroke and combining these two interventions might yield greater therapeutic effects. We aimed to examine whe...
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Article
IDH mutation status prediction by a radiomics associated modality attention network
Isocitrate dehydrogenase (IDH) status is an important factor for the diagnosis of gliomas reported in the 2016 World Health Organization classification scheme for gliomas. There is a strong relationship betwee...
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Chapter and Conference Paper
Robust Zero-Watermarking Algorithm for Medical Images Based on SUSAN-DCT
With the digitization of medical systems, the information security of medical images faces great risks. In order to protect the personal information of patients contained in medical images, this paper proposes...
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Chapter and Conference Paper
An Improved Multi-Instance Learning Model for Postoperative Early Recurrence Prediction of Hepatocellular Carcinoma Using Histopathological Images
HCC(Hepatocellular carcinoma) is one of the primary liver cancer around the world, and it produces a high mortality rate in clinical. Surgical resection is the first-line treatment choice for patients with HCC...
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Chapter and Conference Paper
An Efficient Dual-Pooling Channel Attention Module for Weakly-Supervised Liver Lesion Classification on CT Images
The classification of liver lesions on computed tomography (CT) images is vital for early liver cancer diagnosis. To aid physicians, several methods have been proposed to perform that task automatically. These...
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Chapter and Conference Paper
Iteratively Coupled Multiple Instance Learning from Instance to Bag Classifier for Whole Slide Image Classification
Whole Slide Image (WSI) classification remains a challenge due to their extremely high resolution and the absence of fine-grained labels. Presently, WSI classification is usually regarded as a Multiple Instanc...
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Chapter and Conference Paper
Robust Zero Watermarking Algorithm for Medical Images Based on BRISK-FREAK and DCT
With the development of mobile Internet technology, the technology in the field of medical image processing is constantly updated and iterated. Digital watermarking technology plays an important role in the fi...
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Chapter and Conference Paper
Deep Neural Network-Based Classification of Focal Liver Lesions Using Phase-Shuffle Prediction Pre-training
Computer-aided diagnosis plays an important role in focal liver lesion diagnosis (classification) which is one of the leading causes of death worldwide. Due to their superior performance, deep learning-based f...
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Chapter and Conference Paper
A Robust Watermarking Algorithm for Medical Images Based on DWT-Daisy and Discrete Cosine Transform
With the development of digital medical imaging technology, the transmission of medical data in the network is becoming more and more frequent. In order to protect patients’ privacy information during transmis...
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Chapter and Conference Paper
Teacher-Student Learning Using Focal and Global Distillation for Accurate Cephalometric Landmark Detection
Cephalometric analysis is used frequently by dentists and orthodontists to analyze the role of the human skull in making a diagnosis and formulating treatment plans. To perform such analysis, cephalometric lan...
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Chapter and Conference Paper
A Transformer-Based Model for Preoperative Early Recurrence Prediction of Hepatocellular Carcinoma with Muti-modality MRI
Hepatocellular carcinoma (HCC) is the most common primary liver cancer which accounts for a high mortality rate in clinical, and the most effective treatment for HCC is surgical resection. However, patients wi...
