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40 articles for “fine feature”
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Simulation of Image Processing using Linux Operating Systems
Abstract: AbstractImage processing and restoration through a base image can provide useful information about the scene, such as saliency and depth map. We first apply the geometric transformation algorithm for restoration of the blurred image. As suggested in the base paper that the geometric analysis will provide us the fine feature available in the image, we have utilized this algorithm for the purpose of image restoration. Measuring the amount of blur …
Published in Journal of Advances in Shell Programming · Vol. 7, Issue 3, 2020 · pp. 16–22 Read article
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A Review of Computational Methods for Image Restoration and Noise Reduction Using Reference Images
Abstract: Digital imaging systems play a vital role in numerous application domains, including consumer photography, biomedical imaging, remote sensing, aerial surveillance, and astronomical observation. Despite continuous advancements in imaging hardware and software, the visual data acquired by these systems often suffer from degradation caused by spatially non-uniform blur. This blur may arise due to several factors, such as lens imperfections, atmospheric turbulence, sensor limitations, motion between the camera and the scene, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 23–30 Read article
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Simulation of Image Processing and Restoration Through A Base Image Using Matlab
Abstract: Basically, in image processing the main work is done on pixels and its value. Basically, an image is a two-dimensional function f(x, y), where x and y are spatial coordinates. Here, in the present study geometrical transformation is being used for image restoration and processing. Steps are carried some for the result outcome. First the image is read in the algorithm, further the coordinates and pixels are being specified, and …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 8, Issue 1, 2021 · pp. 31–40 Read article
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Analyzing Potential Leads Data to Improve Marketing Strategies
Abstract: To develop a lead scoring model using multiple machine learning models and create a user-friendly web application, the first step is to clearly define the problem and collect relevant data from various sources such as CRM, website, social media, email campaigns, etc. After cleaning and pre-processing the data, identify the essential features that can affect the lead score and split the data into training and testing sets. Next, select a …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 18–25 Read article
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Aspect-Based Sentiment Analysis Using a Hybrid Approach with Dependency Parsing
Abstract: The rapid expansion of digital communication has resulted in an unprecedented volume of consumer-generated textual data across online reviews, social media platforms, forums, and e-commerce websites. Extracting meaningful insights from this data is increasingly important for organizations seeking to understand customer opinions, preferences, and behavioral trends. Despite significant advances in sentiment analysis, many existing approaches primarily focus on surface-level features and often overlook deeper syntactic and semantic relationships within text. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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Pharmacognostical and Pharmaceutical Analysis of Amavatari Rasa- A Herbo-mineral Compound
Abstract: Amavatari Rasa is a herbo-mineral formulation, composed of processed mercury, sulphar, Terminalia chebula Retz, Terminalia bellerica Roxb., Phyllanthus embilica (Embelica officinalis Gaertn), Plambagozeylenica Linn., Commiphora wightii (Arn) Bhand and Ricinuscommunis Linn. This formulation is routinely practiced in cases of Rheumatoid Arthritis, but preliminary physicochemical and pharmacognostical profiles are not available. Considering this, an attempt has been made to develop this profile. Pharmacognostical study of raw drugs was carried out. Organoleptic …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 7, Issue 2, 2016 · pp. 6–10 Read article
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Improved Melanoma Recognition using Score Fusion Framework based on Deep Classifiers
Abstract: Melanoma is a fast-growing and malignant cancer that affects neural crest-derived cells of the skin. Early detection is the key to survival and rapid recovery; however, typical diagnosis is based on visual inspection by expert dermatologists. Many melanoma recognition methods have been proposed in the literature that can classify lesions, based on hand-crafted as well as deep learning-based features. However, an accurate, automated method for melanoma is still required. This …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 2, 2021 · pp. 25–33 Read article
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Study of Dielectric and Magnetic properties for ZnFe 2 O 4 Nanoparticles Synthesized usinghigh current Exploding Technique
Abstract: The current article uses the exploding wire technique to examine the magnetic, electrical, and dielectric properties of nanoscale zinc copper ferrite (ZnFe2O4). The SEM micrographs confirm the almost uniform size distribution of the nanoparticles. The Mossbauer spectrum of the nanoparticles was recorded with an externally applied magnetic field at room temperature. The ferromagnetic behavior of the ZFO sample was determined through VSM measurements at ambient temperature, and the M-H loop …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 161–166 Read article
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Automatic Chest X-ray Report Generation Using Machine Learning
Abstract: In this study, a deep neural network is suggested for the automatic creation of precise radiologist reports from chest X-ray pictures. The proposed network responds to the need for medical image captioning by learning to extract key features from the image and creating tag embeddings for each patient's X-ray images. Medical image captioning demands coherence and high accuracy in identifying abnormalities and extracting information. For a finer representation, the network …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 1, 2023 · pp. 29–39 Read article
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LLM-based Chatbot for Course-based Question Answering
Abstract: The “LLM-based Chatbot for Course-Based Question Answering” project addresses the pressing need for tailored and efficient learning tools in education. By using a state-of-the-art Large Language Model (LLM) with a diverse dataset, including textbooks, professor slides, and web scraping data, the chatbot offers accurate and contextually enriched responses to students' course-related queries. Using recent advances in language modeling, this work presents a Longformer-based Language Model (LLM) for constructing a smart …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 30–41 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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Accurate & Efficient Plant Disease Detection using Transfer Learning with Edge Impulse
Abstract: Transfer learning is a powerful machine learning technique that allows optimization of pre-trained models for related tasks on small datasets. In this research paper, we explore the application of Edge Impulse & transfer learning for plant diseases and aim to detect on edge devices more effectively at low cost. We collected and preprocessed many plant images and used this data to fine-tune a neural network model pre-trained by Edge Impulse. …
Published in Recent Trends in Sensor Research & Technology · Vol. 10, Issue 1, 2023 · pp. 30–41 Read article
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Substantial Enrichment of Mechanical, Thermal and Electrical Properties of Thermoplastic Polyester Elastomer by Melt Blending with Nano-ZnO
Abstract: Polymers are more reinforced with nano metal oxides, a completely flexible composite of engineering that simplifies the way of exhibiting good mechanical and chemical features. Polymer mixtures represent a very vital field in the handling of innovative ingredients, which have better features than net polymers. Polymer mixtures are able to deliver ingredients with prolonged useful features beyond the range that can be achieved from a single polymer equivalent. A methodical …
Published in Emerging Trends in Chemical Engineering Read article
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Substantial Enrichment of Mechanical, Thermal and Electrical Properties of Thermoplastic Polyester Elastomer by Melt Blending with Nano-ZnO
Abstract: Polymers are more reinforced with nano-metal oxides, a completely flexible composite of engineering that simplifies the way of exhibiting good mechanical and chemical features. Polymer mixtures represent a very vital field in the handling of innovative ingredients, which have better features than net polymers. Polymer mixtures can deliver ingredients with prolonged useful features beyond the range that can be achieved from a single polymer equivalent. A methodical study was performed …
Published in Emerging Trends in Chemical Engineering · Vol. 9, Issue 1, 2022 · pp. 12–22 Read article
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Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach
Abstract: In modern digital signal processing, the capability for denoising and smoothing in real time is very important in scientific, engineering, and industrial applications. This paper presents an efficient hybrid framework that merges two mathematically sound methods, namely, DTT and PDE defined as the Heat Equation, to robustly denoise a signal with minimal distortion. The model addresses one of the most challenging tasks in signal restoration, which maintains the fidelity of …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 9–14 Read article
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Development of Intensity-based Segmentation Technique for Meningioma Tumor Detection in MRI Images
Abstract: There are many types of brain tumors. Some brain tumors detection system using segmentation and classification of MRI images. Brain tumors can have any shape or cut. This encourages us to use high-capacity deep neural networks. Segmentation task and 8000 images for classification task of our neural network and found the best architecture to use. convolutional neural network. In recent years, the three most common forms of brain tumours—glioma, meningioma, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 11, Issue 03, 2022 · pp. 50–54 Read article
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DETECTION OF LUNG CANCER USING SOFT COMPUTING TECHNIQUES
Abstract: Cancer is a generic term that can affect any part of the body. Most cancers, 90%-95%, are because by environmental and lifestyle variables which cause genetic mutations. Inherited genetics account for 5% to 10% of the total. Early identification of lung cancer has improved patient survival and has been a vital study topic. It starts within the cells covering the bronchi and lung parts like bronchioles or alveoli. Due to …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 1–12 Read article