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225 articles for “R-CNN”
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Machine Learning-Driven Polymer Composite Smart Skin for Integrated Sensing in Soft Robotic Systems
Abstract: Soft robotics has grown rapidly, but its progress is still constrained by the limitations of current sensing skins. Most polymer-based sensors provide either flexibility or sensitivity, yet they struggle to deliver real-time communication and adaptive intelligence when deployed in complex robotic environments. This disconnect between material performance and system-level responsiveness forms a critical bottleneck for practical deployment. Existing approaches often treat tactile sensing and wireless communication as separate problems. As …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 121–136 Read article
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Evaluation of composite material based on different phases of Face recognition System
Abstract: Composite materials can indeed play a crucial role in various phases of a face recognition system, offering advantages such as lightweight construction, durability, and tailored mechanical properties. Let's explore how composite materials can be utilized in different phases of a face recognition system. A composite material based different phases of Face recognitions System is software that recognizes or verifies a person based on a digital image or a frame from …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 195–204 Read article
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 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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IoT-Based Emergency SOS System for Post-Accident Assistance
Abstract: The increase in road accidents poses significant challenges for timely medical response, often leading to life-threatening delays. This project proposes an IoT-based accident wound detection system that utilizes a night vision camera mounted on either the interior or exterior of a vehicle. The system aims to detect injuries sustained by individuals during a collision and promptly alert emergency services. By employing a night vision camera, the system can operate effectively …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 11–19 Read article
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Lung Cancer Detection and Classification Using Deep Learning
Abstract: Lung cancer is a disease that can be effectively treated if detected early. Various technologies, such as magnetic resonance imaging, isotopes, X-rays, and computed tomography scans, are employed for diagnosis. One of the most crucial strategies in combating cancer is early detection, which greatly enhances a patient’s likelihood of survival; this is where artificial intelligence plays a significant role. The approach proposed in this study leverages historical medical data to …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 11–17 Read article
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AI Enhanced E-Voting System Securing Elections with Face Recognition and OTP Authentication in India
Abstract: The E-Voting domain seeks to leverage technology to address these issues, enabling citizens to vote securely and conveniently while maintaining the transparency of the electoral process. Machine learning algorithms like Haar cascade and CNN will enhance the system's security, accuracy, and efficiency by leveraging data- driven approaches. Conventional voting techniques frequently encounter obstacles including identity theft, convoluted processes, and hold-ups in the processing of results. This article suggests a complex …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 21–30 Read article
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Real-Time Gesture Recognition with Convolutional Neural Networks
Abstract: Sign language detection plays a pivotal role in bridging communication barriers for the deaf and hard of hearing community. An extensive investigation on the use of convolutional neural networks (CNNs) for sign language recognition is presented in this article. Leveraging the power of deep learning, our research aims to develop an accurate and efficient system capable of recognizing and classifying sign language gestures in real-time. The report begins with an …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 12–18 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
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Matching Minutiae Fingerprint Q-Learning Approach for Detail Coordination: Identifiable Mark Point
Abstract: The use of fingerprints for high-precision recognition and identification of people is one of the most reliable biometric symbols because it is non-invasive. In this paper, we propose an innovative approach to detect details on low contrast resolution image quality of fingerprint images. Existing algorithms are not very susceptible to sound and image excellence due to the lack of level of intensity. We recommend a reliable route to find fingerprints …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 1–15 Read article
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A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics
Abstract: The research is targeted at the creation of innovative solution "Fingerprint Based Blood Group Prediction" for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 9–18 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article
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Face Emotion Recognition to Detect Depression
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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DentiDetect: Dental Diagnosis Powered by Deep Learning
Abstract: Dental X-rays play a crucial role in modern dentistry, enabling dentists to detect cavities, bone loss, and other hidden dental issues that are not easily visible during a routine examination. X-rays offer a clear picture of teeth, bones, and nearby tissues, enabling early identification of issues. This helps create more efficient treatment strategies and improves patient outcomes. Three commonly used types of X-rays include bitewing, periapical, and panoramic. Bitewing X-rays …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 3, 2024 · pp. 21–26 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