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144 articles for “Image Classification”
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Identification and Categorization of Brain Tumors
Abstract: Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Strategic and well-thought-out treatment planning significantly contributes to improving a patient's overall quality of life. Many different imaging techniques, such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and also ultrasound are used to evaluate tumors in different parts of the body, with a focus on using MRI images for brain tumors. It is …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 2, 2023 · pp. 32–37 Read article
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Facial Biometrics for Attendance System
Abstract: This paper discusses the necessity for effective student attendance management systems by proposing a smart attendance management system utilizing biometric technology. It is well recognised that manually recording attendance is time-consuming and error prone. In this study, we propose a Facial Biometrics attendance system that automates attendance process without requiring human intervention. The system consists of a camera placed in the classroom to take pictures of the pupils. Subsequently, the …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 36–44 Read article
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
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Digital Resurrection: Restoring Fragile Documents with OCR
Abstract: In creating a typical Optical Character Recognition (OCR) system, several steps are involved, such as preprocessing, segmentation, feature extraction, and classification. Preprocessing, which is a particularly interesting and challenging aspect of Document Analysis and Recognition (DAR), deals with converting scanned or photographed images containing machine-printed or handwritten text, including numbers, letters, and symbols, into a format that the system can understand. Segmentation is a crucial task in any OCR system, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 29–35 Read article
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Study of Lipid Profile and Its Correlation with Coronary Angiogram Finding in a Tertiary Care Hospital in an Urban Setting
Abstract: Coronary artery disease (CAD) is a major global health concern caused by the constriction or blockage of the coronary arteries, which can result in serious cardiovascular events. This study looks at the relationship between lipid profiles and the severity of CAD as measured by coronary angiography in patients in a tertiary care hospital. The study focuses on dyslipidemia as a major risk factor for CAD, emphasizing the importance of efficient …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 106–118 Read article
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Optimizing Mango Harvest Timing in the Nasik Region (Maharashtra, India) by CNNs (Residual Network 101)
Abstract: The determination of optimal harvest timing is one of the most critical decisions in mango production, directly affecting postharvest quality, market value, transportation resilience, and export readiness. In regions such as Nashik, Maharashtra—one of India’s major fruit- producing belts—the climatic variability, cultivar differences, monsoon patterns, and market- driven pressures make accurate harvest timing essential. Traditional maturity assessment relies on subjective visual inspection, specific gravity, or destructive testing, each of which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 Read article
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Gesture-Based Cursor Control: A Comprehensive Review of Techniques and Applications
Abstract: Although hand gesture detection for man-machine interfaces has advanced recently, many systems still have issues with background and lighting. We have developed a rapid motion history image-based system to categorize dynamic hand motions and a face detection method to adaptively detect skin color. For the up, down, left-, and right-hand gesture classifiers, four sets of haar-like directional patterns were trained. To operate different household appliances, six hand gestures were defined, …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 1, 2025 · pp. 9–13 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Predicting and Prohibiting the Risk of Heart Failure Using Machine Learning
Abstract: It is challenging to estimate the likelihood of complex chronic disease while treating conditions like heart failure. The application of machine learning, an area of artificial intelligence, in cardiovascular care is growing quickly. In essence, it defines how computers classify and understand data, or choose a task with or without human intervention. The theoretical underpinnings of machine learning are models that accept input data (such as images or text) and …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Section Cutting in Histopathology: An Update
Abstract: Histopathology is the microscopic examination of tissues to diagnose and study diseases, more significantly the diagnosis of cancer. It plays a pivotal role in modern medicine, serving as the gold standard for definitive diagnosis in a wide range of conditions. Through meticulous analysis of tissue morphology (structure) and cellular characteristics, histopathology provides crucial information for disease classification, staging, and guiding patient management. In the world of histopathology, where microscopic details …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 1, 2024 · pp. 29–34 Read article
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Sign Language to Speech Translation and Emergency Alert System for Dumb persons using Ml and IOT
Abstract: This project proposes a novel approach for gesture recognition using key point extraction and neural networks. Our proposed system leverages key point extraction techniques to capture fine-grained spatial information from input gestures. These key points are then fed into a neural network model, allowing for automatic feature learning and robust gesture classification. The goal of this project is to integrate OpenCV's computer vision capabilities to build a flexible and effective …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 17–21 Read article
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Identification of Groundwater Potential Zone of Chhatrapati Sambhajinagar Tehsil Using Remote Sensing and GIS Technique
Abstract: Groundwater is one of the most vital and renewable natural resources, playing a key role in sustaining domestic, agricultural, and industrial activities, particularly in semi-arid regions like Chhatrapati Sambhajinagar tehsil in Maharashtra. The growing population, rising water demand, and irregular rainfall patterns have resulted in a pressing need to locate potential groundwater zones for sustainable water management. This research employs Remote Sensing (RS) and Geographic Information System (GIS) techniques to …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 2, 2025 · pp. 61–73 Read article
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ML-Driven Defect Detection in Additive Manufacturing of Polymer Composites Using Thermal Imaging
Abstract: Polymer-based flexible biosensors have emerged as a pivotal technology in continuous health monitoring, yet their deployment in real-world settings is often hindered by undetected micro-defects and signal distortion caused during fabrication or usage. Existing diagnostic frameworks typically rely on post-hoc processing or bulky instrumentation, failing to offer scalable, real-time detection during additive manufacturing workflows. This study introduces an end-to-end, thermographic imaging-integrated framework for in-situ defect identification during the additive manufacturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 201–215 Read article
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Classification of Plant Leaf Diseases Using Deep Learning Concepts
Abstract: Agriculture is vital to the economy of a country like India, where 70% of the workforce is employed in this sector. Plants suffering from illnesses experience a significant reduction in output. Delays in the identification of plant diseases lead to decreased yield and plant mortality. The cost of manufacturing is increased since it takes a big number of experts to manually detect plant diseases over several acres of land. The …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 46–55 Read article