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491 articles for “Detection Challenges”
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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Zika Virus: Long-term Effects and Vaccine Development Efforts
Abstract: Zika virus (ZIKV) is a mosquito-borne flavivirus that gained international concern following the 2015-2016 outbreak in the Americas. Although most ZIKV infections are asymptomatic or mild, the virus presents significant public health risks due to its ability to cause severe neurological complications, especially in pregnant women and their offspring.Congenital Zika Syndrome (CZS) encompasses a range of fetal abnormalities, including microcephaly, vision impairment, hearing loss, and developmental delays. Infants exposed to …
Published in International Journal of Virus Studies · Vol. 2, Issue 1, 2025 · pp. 25–28 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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Role of Solid-State Materials in Development of devices for Internet of Medical Things
Abstract: The Internet of Medical Things (IoMT) represents a transformative paradigm in healthcare delivery, integrating connected medical devices, sensors, and wearable technologies to enable real-time patient monitoring and personalized treatment. Solid-state materials form the foundational infrastructure of IoMT systems, encompassing semiconductors, energy storage materials, sensing materials, and flexible electronics. This article explores the critical role of advanced solid-state materials in enabling miniaturization, energy efficiency, biocompatibility, and enhanced sensing capabilities essential for …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 11–18 Read article
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Comparative Study of Facial Spoofing Detection using CNN Architecture
Abstract: Facial recognition systems face a high risk of security breach due to various facial spoofing attacks. This challenge was addressed by the study of several deep learning models. This study proposes an idea to detect facial spoofing using deep learning architecture to differentiate live faces form various types of spoofed images/videos using different CNN models. In addition, the study seeks to strengthen security measured in facial recognition system demonstrating that …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 9–17 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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Self-Driving Cars and Computer Vision: Enhancing Computer Vision for Autonomous Vehicle Navigation
Abstract: Autonomous vehicles, commonly known as self-driving cars, are transforming the transportation sector by aiming to enhance road safety, ease traffic congestion, and boost overall efficiency. Central to the operation of these vehicles is computer vision, which enables them to perceive and understand their environment. This paper examines how computer vision contributes to the navigation of autonomous vehicles and highlights its continuous developments. Specifically, it examines key challenges such as real-time …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 1–10 Read article
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Innovations in Targeted Drug Discovery for Personalized Medicine
Abstract: Personalized medicine is revolutionizing modern healthcare by custoizing treatment plans to match an individual’s genetic makeup, protein expression, and metabomlic characteristics. Also referred to as precision medicine, this approach seeks to improve therapeutic outcomes, reduce adverse effects, and make efficient use of healthcare resources. The incorporation of various omics technologies—including genomics, proteomics, transcriptomics, metabolomics, and epigenomics—has greatly advanced our ability to understand disease biology and molecular variations specific to each …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 19–41 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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Recent Advances in Nanotechnology-Assisted Liquid Crystal Biosensors for Sensitive and Naked-Eye Detection of Antibiotics
Abstract: The widespread use of antibiotics in healthcare, veterinary medicine, agriculture, and aquaculture has resulted in increasing levels of antibiotic residues in food products and environmental samples, posing significant risks to human health and contributing to antimicrobial resistance. Conventional analytical methods, including high-performance liquid chromatography (HPLC), liquid chromatography–mass spectrometry (LC–MS), enzyme-linked immunosorbent assay (ELISA), and electrochemical techniques, offer excellent sensitivity but require sophisticated instrumentation, skilled personnel, and extensive sample preparation. In …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 2, 2026 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems.Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered nano‑biosensors, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Review: Distribution Generation and Islandin
Abstract: The demand for distributed generation (DG) has increased in recent years and many countries across the world are adopting it due to various factors such as improvements in technologies including renewable energy sources and the efficiency it provides. However, islanding detection is of prime importance as it can be hazardous to the maintenance workers. The increasing use of distributed generation causes more number of parameters to be controlled for the …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 2, 2016 · pp. 45–54 Read article
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Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm
Abstract: Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner's consent and with no intention of paying for the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 21–30 Read article
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A Comprehensive Study Utilizing Patterned Fabric Images and Detection Techniques with OpenCV and Edge Detection
Abstract: This project offers a comprehensive overview of recent advancements in autonomous fabric failure detection methods, a critical aspect of quality control in the textile industry. Detecting flaws in fabric is an increasingly vital automation challenge. The project evaluates the effectiveness of a proposed method by analyzing patterned fabric images featuring typical flaws. The performance of the proposed approach is assessed across various types of fabric flaws. Additionally, the project tests …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 11, Issue 1, 2024 Read article
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Association Rule Mining for Predicting Heart Disease: Challenges and Opportunities
Abstract: The exponential growth of digital healthcare data has spurred innovative applications of data mining techniques in medical research and practice. Among these, association rule mining stands out for its ability to uncover meaningful correlations within diverse datasets, such as electronic health records, imaging data, and genetic information. This paper reviews the application of association rule mining in predicting heart diseases, emphasizing its potential to enhance early detection, risk stratification, and …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 29–34 Read article
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Emerging Paradigms: Leveraging Artificial Intelligence and Machine Learning for Enhanced Wireless Network Security
Abstract: Wireless networks have now become an indispensable component of our contemporary communication infrastructure, offering both connectivity and convenience. Nonetheless, the increasing complexity and constantly evolving nature of wireless networks present substantial security challenges. This work investigates the utilization of artificial intelligence (AI) and machine learning (ML) techniques to tackle these security issues in wireless networks. We delve into the principles and practices of applying AI and ML algorithms to enhance …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 18–25 Read article
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Revolutionizing Plant Disease Detection: A Comprehensive Review
Abstract: Rise in population demands more food production but the diseases in plants contribute to loss. The advancement in agricultural field has a remarkable effect in detecting plant diseases. These diseases will have a major impact on the quality of plant and yield and hence can destroy the entire plant if they are not controlled on time. To reduce disease-related losses, it is necessary to identify different types of diseases and …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 44–55 Read article
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A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article