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264 articles for “classification models”
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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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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Efficient Energy Management using Artificial Intelligence (AI) and Machine Learning (ML) in Chemical Industry
Abstract: The globe is moving toward higher usage of renewable energy sources, particularly solar and wind energy, as a result of depleting fossil fuel supplies and growing environmental concerns. There are several forecasting methods available for effective wind energy utilization. This review uses algorithms for predicting solar and wind energy as well as artificial intelligence (AI) techniques. A wind-coal coupling energy system planning scheme was designed to lower the high energy …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 33–50 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 Read article
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 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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Machine Learning Techniques for Predicting Industries Based on Region
Abstract: In recent years, there has been a growing interest and emphasis on agricultural land preparation and its implementation among researchers, primarily due to various factors. These factors include an increased focus within the research community, a rising demand for agricultural land, and the significance of assessing soil health for ensuring robust crop production. Picture request is one such philosophy for soil and land prosperity examination. It is a staggering measure …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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A Systematic Study of AI-Powered Robotics for Ocean Cleanup of Plastics
Abstract: The escalating crisis of plastic pollution in marine ecosystems demands innovative solutions beyond conventional cleanup methods. This paper presents a systematic study of artificial intelligence (AI)-powered robotics for ocean plastic cleanup, evaluating their efficiency, technological advancements, and challenges. Autonomous systems, such as AI-driven surface drones (ASVs), underwater robots (autonomous underwater vehicles/remotely operated vehicles [AUVs/ROVs]), and swarm robotics, leverage machine learning (ML) and computer vision to detect, classify, and collect plastic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Nitrosamine Accumulation, Processing Variables, and Indigenous Plant Inhibitors in Nigerian Traditionally Processed Meats
Abstract: N-nitrosamines are classified as probable or possible human carcinogens by the International Agency for Research on Cancer. Carcinogenic N-nitrosamines — principally N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) — are formed in abundance during the preparation of widely consumed Nigerian traditional processed meats including suya, kilishi, and balangu. This original investigation combined a six geopolitical zone of Nigerian market survey with laboratory-controlled model system experiments, effects of processing parameters on N-Nitrosamine formation …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 61–72 Read article
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Physicochemical Transitions and Polymerization Dynamics in Multi-Generational Dentin Adhesives: A Critical Review of the Resin-Dentin Composite Interface
Abstract: Adhesive dentistry has undergone a transformative refinement over the past three decades, transitioning from technique-sensitive, multi-step etch-and-rinse protocols to streamlined universal formulations. This narrative review critically synthesizes evidence from thirty peer-reviewed investigations to evaluate the evolution of dentin bonding agents from the fourth through the eighth generations. The analysis places particular emphasis on the physicochemical dynamics of the resin-dentin interface, including interfacial bond strength metrics, marginal integrity, and microleakage behavior. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 209–228 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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IoT-Based Structural Health Monitoring and Damage Detection in Fiber Reinforced Polymer Composite Structures
Abstract: Applications of fiber-reinforced polymer (FRP) composite in the aerospace, civil infrastructure and renewable energy systems are increasing due to the fact that the composite possesses high ratio of strength to weight and can resist corrosion. However, processes of internal damages such as the cracking of the matrix, delamination and fiber fracture, are likely to take place without being visible on the surface and therefore a periodic check of the structure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1076–1100 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 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
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Melanoma, a fatal type of skin cancer, is a major global health concern. For better patient outcomes, early and precise detection is essential. A branch of artificial intelligence called deep learning has demonstrated encouraging outcomes in medical image analysis, particularly the identification of skin cancer, in recent years. We present a new method for detecting melanoma skin cancer in this paper by utilizing the ResNet-50 architecture, a deep convolutional neural …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 · pp. 1–9 Read article
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Integrated Polarimetric-Interferometric Fusion for Heterogeneous Urban Signature Extraction
Abstract: Mapping heterogeneous urban environments using conventional Synthetic Aperture Radar (SAR) backscatter intensity frequently produces classification errors due to spectral similarity between sparse built-up features, bare soil, and dry vegetation a challenge especially acute in semi-arid Deccan Plateau settings. This research presents a dual-path Pol- InSAR fusion framework that integrates polarimetric scattering decomposition and interferometric coherence stability to extract heterogeneous urban signatures over Beed Taluka, Maharashtra (area: 1,561.31 km²). A temporal …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Live Integrated Facial Observation (L.I.F.O.)
Abstract: A human face is the most influential part of humans that can uniquely identify a person. Using all the facial characteristics as biometric, the LIFO system can be applicable in many different ways. Like in everyday life, the most mandatory task in any organization is attendance marking. Earlier, people used to mark their presence using paperwork but now along with the advancement of technology, this system has also changed and …
Published in Journal of Advancements in Robotics Read article
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Aerodynamic Effects of Wind on Multi-Story Structures: A Height- and Terrain-Based Analysis
Abstract: Wind loads are a critical consideration in the structural design of buildings, with direct implications for safety and serviceability. This study investigates the aerodynamic behavior of reinforced cement concrete (RCC) buildings under varying heights and terrain conditions, in accordance with IS: 875 (Part 3): 2015. 12 structural models representing 20 m, 35 m, and 50 m tall buildings were analyzed using extended three-dimensional analysis of building system (ETABS) across four …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 1–14 Read article