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1364 articles for “deep”
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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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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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Role of Nail Filer Assisted Dermabrasion in Scald Burns
Abstract: Deep second-degree and full-thickness burns tend to heal slowly and often result in scarring. To encourage proper healing, deep dermal burns need to be treated early with tangential excision and skin grafting. While superficial burns, which affect only the epidermis and upper dermal layers, can often be managed with wound irrigation, debridement, and basic wound care, deeper burns that extend into the lower dermal layers and beyond typically require more …
Published in Research and Reviews : Journal of Surgery · Vol. 13, Issue 3, 2024 · pp. 6–10 Read article
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IoT-based Patient Fall Detection and Alerting System for Patient Safety
Abstract: This paper presents an Internet of Things (IoT) based patient fall detection and alerting system designed to enhance patient safety in healthcare settings. Falls among patients, especially in hospitals or care facilities, can lead to severe injuries and complications. The proposed system utilizes wearable sensors integrated with IoT technology to continuously monitor the movements and activities of patients. Machine learning algorithms are employed to analyze sensor data in real time, …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 9–14 Read article
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AI-Powered Fire Detection System for Accurate and Timely Emergency Response
Abstract: AI-based fire detection system leverages deep learning and Open CV. Issues with conventional fire detection techniques include false alarms and expense. The proposed system uses deep learning for real-time fire detection in videos, enhancing accuracy and adaptability. OpenCV aids in crowd counting, improving situational awareness during emergencies. This innovation promises to revolutionize fire safety by offering timely and precise detection, potentially saving lives and property. Additionally, by counting crowds, the …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 30–36 Read article
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Mysticism and Mind: A Critical Review of Parapsychological Studies in India
Abstract: Parapsychology holds a unique place in India, shaped by the country’s rich spiritual traditions and deep-rooted mysticism. The review aimed to look at how the field has evolved in India, blending with cultural beliefs and being subject to scientific scrutiny. It highlights the connection between ancient spiritual practices like meditation, yoga, and the third eye, and modern research into phenomena like extrasensory perception (ESP), telepathy, and psychokinesis. This review paper …
Published in International Journal of Education Sciences · Vol. 2, Issue 1, 2025 · pp. 29–33 Read article
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Sign Talk for Blind and Deaf Translating Hand Gestures into Audible and Textual Communication
Abstract: Sign language serves as a vital communication method for individuals who are deaf or have hearing impairments. It relies on hand gestures, facial cues, and body language to convey messages and express meaning. However, many people who do not know sign language find it hard to communicate with sign language users. The latest progress in artificial intelligence and computing has enabled the creation of systems that can automatically recognize sign …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 20–26 Read article
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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 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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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Generative AI for VR: Creating Physically Realistic Models
Abstract: Virtual Reality has revolutionized the traditional learning system by creating and interactive and engaging environment. However, its ability to show precise real-world experiences is limited due to lack of physical realism. This study investigates the potential of Generative Adversarial Network (GAN) in creating physically realistic 3D models. Proposed system incorporates deep learning techniques along with physics-based constraints to enhance model’s accuracy and usability. To achieve this, experiments were conducted on …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 14–22 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Artificial Intelligence and IoT Integration for Real-Time Violence Monitoring
Abstract: The peace and tranquility of any place can be affected greatly by the insurgence of violence and violent attacks that are perpetrated by individuals with malicious and nefarious intentions. These individuals terrorize the areas and can cause a lot of harm and damage to people and public property. The incidences of violence are undesirable and can be problematic to handle by the law enforcement agencies, as these acts are committed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 39–45 Read article
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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Geotechnical study of a landslide reactivation in clay soils (central Piedmont, NW Italy).
Abstract: In March 2015, exceptional meteoric events occurred in southern Piedmont caused a remarkable rise of the rivers water level of the Tanaro Basin with flooding and many landslides. The engineering geological study reported here, concerns a triggering of a previous landslide occurred in 1982 in the hills, shaped in the marine sedimentary succession (Lugagnano Clay, lower Pliocene) of the southern Asti Reliefs, near San Martino Alfieri village. Detailed geological, morphological …
Published in Journal of Geotechnical Engineering · Vol. 7, Issue 1, 2020 · pp. 21–36 Read article
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Study of Applications of Artificial Intelligence in Nuclear and Particle Physics
Abstract: Abstract This article explains the main concepts of the artificial intelligence, focusing on its history, its types and applications in Nuclear & Particle Physics. Deep learning method employs nonlinear functions to adjust the weight of the data wanted from the data background. By extracting meaningful data and fitting its shape with parameterized functions, deep learning method can capture main rules of the rude data, and make reliable predictions based on …
Published in Journal of Nuclear Engineering & Technology · Vol. 9, Issue 1, 2019 · pp. 29–33 Read article
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Wind Turbine Operation Information System
Abstract: The ability of wind energy to produce energy steadily and consistently makes it an important and necessary energy source. However wind energy has faced many challenges, such as discontinuation of wind farm equipment, early investment costs and therefore finding wind energy efficiency areas. The main aim of this project is to determine the energy efficiency of wind turbines, and it will also help to make suggestions to reduce the maintenance …
Published in Trends in Machine design · Vol. 10, Issue 3, 2023 · pp. 40–46 Read article
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A Study to Assess the Effectiveness of Health Instruction Module (HIM) on Knowledge Regarding Varicose Vein and DVT and its Preventive Measures Among Laborers in Selected Small Scale Industries at Greater Noida
Abstract: Varicose veins square measure veins that became enlarged and tortuous. The term usually refers to theveins on the leg, though unhealthy veins will occur elsewhere. Veins have leaflet valves to stop bloodfrom flowing backwards (retrograde flow or reflux). Leg muscles pump the veins to come back bloodto the Heart (the calf muscle pump mechanism), against the results of gravity. When veins becomeunhealthy, the leaflets of the valves now not meet …
Published in Journal of Nursing Science & Practice · Vol. 11, Issue 2, 2021 · pp. 6–22 Read article
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Neural Sheath Liposarcoma: A Case Report
Abstract: Liposarcoma is a malignant mesenchymal tumor of the adipose tissue [1]. Liposarcomas most frequently arise from the deep-seated stroma rather than the submucosal or subcutaneous fat [2]. The most recent World Health Organization classification of soft tissue tumors recognizes five categories of liposarcomas: (1) well differentiated, which includes the adipocytic, sclerosing, and inflammatory subtypes; (2) de differentiated; (3) myxoid; (4) round cell; and (5) pleomorphic [2–4]. The anatomical distribution of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 2, Issue 3, 2012 · pp. 8–10 Read article