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Multimodal Information Retrieval
In today’s rapidly evolving digital landscape, the wealth of available information has expanded beyond the boundaries of traditional text-based...
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Retrieval Augmented Modeling
Till this point in our book, we have discussed the fundamental principles of information retrieval, exploring its key elements, and various...
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Outlook
While multimodal information retrieval has several exciting applications and a high potential for impact on important problems, there are several...
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Multimodal Content Generation
In this chapter, we will review the advances that are being made in this new field of multimodal content generation and also discuss several...
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Transformer-Driven Models for Language, Vision, and Multimodality
In this chapter, we will learn about the modeling and learning techniques that drive multimodal applications. We will focus specifically on the...
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Introduction
In this book, our emphasis is on multimodal information retrieval, specifically concentrating on text and image data. The traditional unimodal...
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State of the Art Analysis of Word Sense Disambiguation
Word Sense Disambiguation (WSD) is a computational activity in natural language processing (NLP) that aims to determine the meaning of a word in its...
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Alzheimer’s Disease Detection Using Convolution Neural Networks
Millions of people throughout the world are afflicted by the progressive neurological condition known as Alzheimer’s Disease (AD). Analyzing MRI...
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Application of Deep Learning Techniques for Coronary Artery Disease Detection and Prediction: A Systematic Review
Coronary artery disease, a leading cause of death, occurs when coronary arteries narrow due to plaque or blood clots. It is possible to visualize...
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Machine Learning Based Delta Sigma Modulator Using Memristor for Neuromorphic Computing
This paper presents a memristor-based delta sigma modulator that mimics a human brain neuron for artificial neural network training. Memristive...
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Modeling and Design of an Autonomous Amphibious Vehicle with Obstacle Avoidance for Surveillance Applications
The autonomous vehicle system is built on the autopilot technique, allowing the vehicle to operate without human intervention. Equipped with sensors...
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Rapid Damage Detection Using Texture Analysis with Neural Network
Damage detection in many contexts, such as buildings, infrastructure, and natural landscapes, must be done quickly and accurately for successful...
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Prediction of Cardio Vascular Diseases Using Calibrated Machine Learning Model
Cardio Vascular Disease (CVD) uncovers various conditions that influence Heart Attack and cause more death rates in the recent decades. It is the...
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Maritime Vessel Segmentation in Satellite Imagery Using UNET Architecture and Multiloss Optimization
Detection of ships and precise recognition within expansive remote sensing images constitutes a pivotal research avenue within the domain of remote...
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An Improved Filter Based Feature Selection Model for Kidney Disease Prediction
In terms of societal health threats, kidney disease has been viewed as an increasing threat in the modern day. With an increasing incidence, chronic...
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A Novel Approach to Address Concept Drift Detection with the Accuracy Enhanced Ensemble (AEE) in Data Stream Mining
Data streams present a unique challenge in effectively managing concept drift, making data mining a complex task. To overcome these challenges and...
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Dysarthria Speech Disorder Assessment Using Genetic Algorithm (GA)-Based Layered Recurrent Neural Network
A speech issue known as dysarthria occurs because of muscular weakness and nerve damage following a stroke, an infection in the brain, or a brain...
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An Integrated Method to Monitor Indoor Air Quality Using IoT for Enhanced Health of COPD Patients
Respiratory morbidity and mortality are linked to outdoor air quality. People with COPD and other populations that are susceptible to outdoor air,...
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Artificial Intelligence in Breast Cancer Diagnosis: A Review
The impact of human errors in imaging interpretation and the fact that decision support systems can improve the reliability and accuracy of radiology...
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Classification of H&E Stained Liver Histopathology Images Using Ensemble Learning Techniques for Detection of the Level of Malignancy of Hepatocellular Carcinoma (HCC)
Hepatocellular carcinoma (HCC) is one of the most common types of primary liver cancer and a leading cause of cancer-related deaths worldwide....