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238 articles for “Deep Convolutional Neural Network”
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article
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Automatic Image Description Generation Using Deep Learning Techniques
Abstract: Automatic Image Description Generation methods are extremely useful for image retrieval, search and organization. Previous approaches either use the existing labelled dataset to compose sentences or compose a new description for the test image by exploiting available descriptions of the training images. In practice these methods have limited accuracy, hence if the most important objects in an image cannot be identified, then they cannot generate valid description. Another difficulty lies …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 6, Issue 1, 2019 · pp. 28–37 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Detection of Driver Emotion Using Deep Learning
Abstract: High level Driver-Help Frameworks (ADASs) are utilized for expanding security in the auto space, yet momentum ADASs quite work without considering drivers' states, e.g., whether she/he is genuinely able to drive. Feelings are a significant way of behaving of people and may emerge in driving circumstances. Uncontrolled feelings can prompt unsafe impacts. To control and decrease the adverse consequence of conduct. In this paper we will distinguish the driver’s conduct. …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 01–06 Read article
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A Deep Survey on Techniques Used to Recognize Locust Based on CNN
Abstract: The major threat in agriculture is insect pests and crop disease. Outbreaks and upsurges of insects can cause huge loss to crop production. Locusts are crop devouring pests found in many parts of the world. Recognition of locusts in early stage helps to prevent the spread of locusts by taking appropriate counter-measures and biological control methods. Initially, locusts were classified and recognized manually which is time consuming and requires taxonomic …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 1–8 Read article
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Flora-Vision: A Quality Assurance System For The Pharmaceutical Industry
Abstract: In contemporary pharmaceutical production, the persistent challenges of manual labor, human error, and contamination risks pose significant obstacles to efficiency and product quality. Particularly in sectors such as Ayurvedic products, cosmetics, and medicines, the need for innovation is pressing. Revolution in production process can be addressed by introducing innovative solutions and thereby challenges could be overcome. Through the utilization of advanced technology, the proposed system streamlines sample management and quality …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 53–60 Read article
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Diagnosing Pneumonia from Chest X-rays Using Deep Learning Algorithms Through Convolutional Neural Network, Transfer Learning and Fine Tuning
Abstract: Pneumonia is an inflammatory condition of the lungs that induces air sacs which leads to a contagious infection of lungs. Patients who are afflicted with the virus can be saved from death and the virus can be eradicated from spreading further through effective diagnosis. X-rays of the chest are frequently used to diagnose pneumonia. Detecting pneumonia from a Chest X-ray is typically slow and inaccurate. It is essential to identify …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 8–16 Read article
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Plant Disease Detection
Abstract: Plant growth is a crucial requirement for farmers since it provides a pathway for their livelihood. Plant damage and growth are correlated with one another. Despite their best efforts, farmers frequently fail to grow healthy crops because of ill plants. Plant disease is currently a dangerous problem for farmers, customers, the environment, and the global economy. Major health problems in plants are caused by excessive pesticide use. Image processing may …
Published in Recent Trends in Programming languages · Vol. 9, Issue 3, 2022 · pp. 59–66 Read article
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Deep Learning Algorithms for Medical Image Encryption to Ensure Secure Data Transfer
Abstract: Deep learning has significantly impacted various fields, including medical imaging, by offering new ways to encrypt medical images for secure data transfer. This research work examines how deep learning algorithms are used to enhance medical image security during transmission. Given the high sensitivity and privacy requirements of medical data, it’s crucial to maintain its confidentiality. Traditional encryption techniques, while reliable, often struggle with issues like scalability, computational efficiency, and the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 28–36 Read article
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Multinomial classification Identification for Domestic Violence Virtual Posts Based on Improved Convolution Neural Network (ICNN)
Abstract: AbstractDomestic violence isn’t only about the physical violence but further any conduct the purpose of which is to gain power and manage over a spouse, partner, girl/boyfriend or intimate own circle of family member which leads to the violation of human rights. Through the web-based networking media domestic violence crisis support (DVCS) have demonstrated fundamental help directions to abused people and their families. The unrivaled outcomes in online content description …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 1–10 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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Breast Cancer Detection and Multiple Classification Using CNN
Abstract: Although some efforts have been made in the form of preventative screening programs, breast cancer remains one of the rising causes of death in women. Computer-assisted diagnosis is needed because of the rapidly increasing number of mammograms that can be collected by these programs. Performance metrics are not significantly improved by computer aided detection methods designed to improve diagnosis without a large number of sequential readings. In this context, self-imaging …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 2, 2023 · pp. 28–38 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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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 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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COVID-19 Detection through Deep Learning Models using Chest X-ray
Abstract: Detection of COVID-19 in a minimum amount of time is one of the biggest challenges in front of us because COVID-19 is a rapidly spreading disease. Patients are increasing in a rapid amount of time. Hence, we proposed an AI-technique based deep-convolutional neural network to detect COVID-19 patients using real-world data. In our proposed system, chest X-ray images are used to find out COVID- 19 patients. X-rays are available very …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 2, 2021 · pp. 11–16 Read article
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Remote Healthcare Diabetic Retinopathy Detection Using Deep Learning
Abstract: High blood glucose levels are a hallmark of diabetes mellitus (DM), a metabolic disease. This can give rise to a range of complications, with Diabetic Retinopathy (DR) being among them. DR can impair vision and, if not addressed, may lead to a loss of eyesight. Symptoms include aberrant blood vessels, fluid leaks, exudates, haemorrhages, and retinal microaneurysms. With the advancement of technology, medical imaging has become one of the most …
Published in Journal of Open Source Developments · Vol. 10, Issue 2, 2023 · pp. 42–47 Read article
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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 Read article