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78 articles for “App segmentation”
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Automatic Number Plate Recognition Based Image Processing
Abstract: In most countries, traffic control and vehicle owner identification have become important problems. It is almost impossible to identify vehicle owners who break rules of the traffic, especially those driving at high speeds. Another problem inhibits traffic officers from catching the offenders in most cases because solving traffic offenders involves retrieving license plate numbers from fast-moving vehicles. Automatic Number Plate Recognition (ANPR) systems have been developed as an effective solution …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 33–40 Read article
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Advancing Brain Tumor MRI Segmentation
Abstract: Segmentation of brain tumors in MRI scans is an integral part of neuroimaging carried out for diagnostic and therapeutic interventions. Given that manual segmentation is cumbersome and highly variable, there arises a need for automated, more precise segmentation solutions. This project, ‘Machine Learning and Deep Neural Networks to Advance Brain Tumor MRI Segmentation’ will develop a better, efficient, and accurate segmentation model to help clinicians identify brain tumors with greater …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 28–33 Read article
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Effectiveness of Online Advertising in Reaching Target Audiences
Abstract: This study examines the effectiveness of online advertising in reaching target audiences. With the rapid growth of digital platforms, understanding the efficacy of online advertising has become paramount for marketers. Utilizing a combination of quantitative analysis and case studies, this research investigates the various strategies and channels employed in online advertising to reach specific demographic segments. By analyzing metrics such as click-through rates, conversion rates, and audience engagement, this study …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 14, Issue 2, 2024 · pp. 8–12 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 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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Wave plate; what is the angle of its central curved segment which provides biomechanically optimal stability for femoral shaft fracture?:A 3-D Finite Analysis
Abstract: Even though intramedullary nailing of femoral shaft fracture is the standard surgical treatment as it is in tibial fracture, plate fixation might be a choice when the fracture involves open growth plate, patients are of shorter stature or have narrow canals. In these cases, fixation techniques with plate and screws, for example, percutaneous procedures involving wave plate, are useful thanks to minimal invasion and preservation of biological environment surrounding the …
Published in Research and Reviews : Journal of Surgery · Vol. 13, Issue 1, 2024 · pp. 31–43 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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AI-Driven Promotion Platforms: Increasing Customer Engagement in Banking
Abstract: Artificial Intelligence has been in talk since data was considered as an asset. Using this data, prolific information has been extracted to gather detailed information and create datasets. Artificial intelligence is shaping the narrative of the world in the 21st century. It has become a driving force behind innovation, influencing various industries and redefining traditional practices. Artificial intelligence has revolutionized customer engagement strategies across industries, particularly Banking. This study explores …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 87–92 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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Innovations in Forensic Imaging: Leveraging Deep Learning for Authenticity Verification
Abstract: The advent of digital media has necessitated advancements in forensic imaging, especially for the detection and verification of image authenticity. In this context, digital image forensics plays a critical role in identifying manipulated or counterfeit images. This paper presents a new method that uses deep learning techniques to enhance image forgery detection. The approach utilizes a convolutional neural network (CNN) to automatically learn and recognize the intricate features present in …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 2, 2024 · pp. 28–33 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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Design and Performance Evaluation of PLA-based Umbrella Wheels for Stair-Climbing Robotic Applications
Abstract: Staircase climbing robots require a complex design capable of navigating various stair configurations. A crucial component of such robots is the wheel mechanism. This paper focuses on the umbrella wheel mechanism and its application in staircase climbing robots. In this study, a PLA–based umbrella wheel structure is developed and fabricated using fused deposition modeling (FDM) for application in stair-climbing robots. The umbrella wheel geometry enables transformation from a circular rolling …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 808–824 Read article
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Crypto Talk Voice Shield: Secure Speech Communication System Using Arduino
Abstract: In the rapidly evolving landscape of communication security, this study presents a system designed around Arduino Uno technology, specifically engineered for the secure encoding, transmission, and decoding of speech data. By integrating advanced encryption algorithms, the system ensures that speech data is transmitted in segmented bit chunks, each enveloped in multiple layers of security to prevent unauthorized access or interception. This multi-tiered encryption approach establishes a highly secure communication channel, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 1, 2025 · pp. 23–30 Read article
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A Survey of Seasonal-based Movie Recommendations Using Machine Learning Through a Hybrid Approach with User Interest in Various OTT Platforms
Abstract: No matter their age, gender, race, color, or region, everyone enjoys watching films particularly during festival season. We are all, in the most basic sense, connected to one another through this beautiful medium, but what really grabs attention is the fact that, regardless of how unique our choices and combinations are in terms of picture show preference, one thing remains constant. Certain people have a preference for certain types of …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 24–29 Read article
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Optical Image Sensing and Analysis of Iron Ore Pellets: A Machine Learning Approach
Abstract: The present work is aimed to improve quality control in steel production using SEM imaging and machine learning. High-resolution SEM images of iron ore pellets, primarily composed of hematite and magnetite, are analyzed to understand their microstructural features, which significantly impact pellet performance during reduction processes. Traditional microstructure analysis is manual, time- consuming, and prone to inconsistencies. This study proposes an automated approach using K-Means Clustering, Canny Edge Detection, DBSCAN, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 7–18 Read article
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Image Processing and Deep CNN-based Automatic Liver Cancer Detection
Abstract: Liver cancer ranks among the leading causes of mortality for people worldwide. In the current situation, manually identifying the cancer tissue is a challenging and timeconsuming task. Treatment planning, response monitoring, tumor load assessment, and prediction are all made possible by the segmentation of liver lesions in CT scans. To address the current problem of liver cancer, the Hybridized Fully Convolutional Neural Network (HFCNN), which has been theoretically modeled, has …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 39–41 Read article
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Survey on Retinal OCT Image Preprocessing, Segmentation, and Deep Learning Based Classification
Abstract: Optical coherence tomography (OCT) is a non-invasive technique that generates high-resolution, detailed cross-sectional images of biological tissues. By utilizing low-coherence interferometry, OCT enables visualization of tissue microstructure with micron-scale resolution, making it useful in various medical fields such as ophthalmology, cardiology, and dermatology. In ophthalmology, OCT is extensively used for diagnosing and monitoring retinal diseases like macular degeneration and diabetic retinopathy, allowing doctors to assess changes in tissue morphology over …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Analysis of a Battery Pack Module for a Formula Student Car
Abstract: This research aims to evaluate the development of a high-voltage accumulator system that meets established standards of safety and operation. It examines key components, protocols, and techniques used in its creation while assessing performance in electronic cooling and structural integrity. Polymers, serving as electrical insulators and flame retarders, have found an interesting application in EV battery packs. This study focuses on polycarbonate materials' ability to withstand thermal and structural loads …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 320–339 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article