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216 articles for “Features extraction and Detection”
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Efficient Object Detection Based on Local Invariant Features
Abstract: Object detection is an important task in image processing and computer vision. Binary Robust Invariant Scalable Keypoint (BRISK) local features are extracted from the object. These features are invariant to image scale, translation, rotation, illumination and partial occlusion. Object detection process begins by matching individual features of the user queried object to a database of features with different objects which are saved in advance. Cite this Article:Anand Rathod, Manoj Bagale, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 1–3 Read article
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Voting Based Classification Method for COVID-19 Prediction
Abstract: COVID-19 dataset comprises date, country, confirmed cases, recovered cases and total deaths. The data is integrated with climate data consisting of humidity, dew, ozone, perception, maximum temperature, minimum temperature, and UV. The artificial intelligence based COVID-19 diagnosis strategies can generate more accurate results, save radiologist time, and make the diagnosis process cheaper and faster than the usual laboratory techniques. The COVID-19 detection has various phases which include pre-processing, feature extraction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 2, 2021 · pp. 34–41 Read article
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A Novel Technique to Detect Plant Disease
Abstract: One of the important sectors of Indian Economy is Agriculture. Employment to almost 50% of the countries workforce is provided by Indian agriculture sector. India is known to be the world’s largest producer of pulses, rice, wheat, spices and spice products. Therefore, in field of agriculture, detection of disease in plants plays an instrumental role. Plants are highly prone to diseases that affect the growth of the plant, which in …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 10–16 Read article
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Ocean Surface Features Extraction using Morphological Techniques from Sentinel-1A Data
Abstract: SAR (Synthetic Aperture Radar) imagery of the ocean surface obtained from remote sensinginstruments is one of the prominent research areas. In this paper, detection of oceanicfeatures from SAR using morphological technique is proposed. The detected surface featuresare presented in layered form. The main advantage of such representation is features can beeasily enabled or disabled on SAR image. Algorithm is tested on Sentinel-1A dataset of oceansurface.Keywords: SAR Images, Surface Features, Layered …
Published in Journal of Remote Sensing & GIS · Vol. 11, Issue 2, 2020 · pp. 1–4 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Generation of Facial Expressions through Manipulating Facial Parameters
Abstract: Extracting discriminative features from salient facial patches plays an important role in effective facial expression recognition. The accurate detection of facial landmark needed to improve the localization of the salient patches on face images. This paper proposes framework for expression recognition by using appearance features of facial patches. By synthesize of emotional facial expressions through manipulating facial parameters, we aim to introduce facial emotion to a neutral facial image. For …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 2, 2016 · pp. 33–38 Read article
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Biomedical Image Processing: Retinal Blood Vessel Segmentation using Graph Cut Technique
Abstract: Retinal image, which is used in determining different diseases in the eye of a human being, is an important feature in the field of ophthalmology. Similarly, optic disc detection is also an important feature as it locates diseases and defects. In Image processing of fundus, image vessel extraction is the key feature used in doing so. Here, we are presenting the Graph Cut method which helps in extracting blood vessels …
Published in Current Trends in Signal Processing · Vol. 5, Issue 1, 2015 · pp. 17–20 Read article
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License Plate Detection using CNN
Abstract: Tag recognition is a picture preparing innovation used to distinguish vehicles by their tags. This advancement is used in various security and traffic applications. Deep learning employs complex mechanisms to extract features from samples This paper proposes a system trained using the MobileNetV2 convolutional neural network (CNN) model to detect the characters and digits from vehicle license plates. Our approach is highly influenced by the recent advancements made in the …
Published in Journal Of Network security · Vol. 9, Issue 2, 2021 · pp. 21–27 Read article
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Vehicle Insurance Fraud Detection Using Supervised Neural Network Model
Abstract: Vehicle insurance fraud is a serious problem that causes huge financial losses to insurance companies. In recent years, developing fraud detection models using machine-learning techniques has been of great interest. This study proposes a novel approach for vehicle insurance fraud detection using Supervised Neural network model on the Kaggle Vehicle Insurance Fraud Detection dataset. The initial step in this study involves performing data pre-processing and feature extraction on the dataset, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 10, Issue 1, 2023 · pp. 32–39 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
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Analysis of Side View Face Recognition Using Gabor Filter and PCA Techniques
Abstract: AbstractRecognition of human side face is being a dynamic research area in recent era. A different system for face recognition including side view confront has been proposed in this paper. Face recognition utilizing blocked face or using a small portion of the face is still an issue in human recognition which has incredible potential in criminological and security applications. The paper gives a concise thought regarding PCA and 2DGF systems …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 2, 2017 · pp. 21–27 Read article
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Design and development of an IP core for speech detection in varying noise environments
Abstract: Speech detection is a process of separating speech and silence regions from noisy speech. It is an important part in speech processing. One of the important and difficult tasks in speech detection is the detection of speech in a very low signal to noise ratio. The application of speech detector includes speech coding, where the accurate speech coding can reduce bit number low down the bit rates, and in speech …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 7, Issue 1, 2020 · pp. 19–27 Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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IoT-Enabled Self-Monitoring Polymer Composites for Solar Facade Systems with Cloud-Based Thermal Analytics
Abstract: The increasing demand for intelligent and energy-efficient building systems has hastened the production of smart solar facade systems. This paper presents an IoT-based self-monitoring polymer composite system, which includes thermal analytics running on the cloud to provide real-time assessments of the performance of the facade. The artificial composite panel has sensing capability built in which the material is able to measure both surface and internal thermal behavior simultaneously in dynamic …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 657–681 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Detection of Facial Parts based on ABLATA
Abstract: Facial feature detection from standard 2D RGB images is a well-researched field but out of prolific techniques there isn't much efficacy is achieved in the previous studies that can extract feature data even for a low quality images in real time. Hence, we propose an algorithm based on Attribute Based Level Adaptive Algorithm (ABLATA) which use recursive data estimates for this task. While the recursive data estimates learns the relation …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 36–41 Read article
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Cyberattack Detection System in Private Cloud
Abstract: As cloud computing adoption in colleges continues to rise, the security of private cloud systems has become a paramount concern. Data breaches resulting from cyberattacks can inflict severe damage to a university's revenue and reputation. This research proposes a novel machine learning-based cyber threat detection system tailored to the university's private cloud environment. The system's main objective is to continuously monitor the cloud infrastructure and employ advanced machine learning algorithms …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 2, 2023 · pp. 37–44 Read article
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Innovative Eyewear for the Visually Impaired
Abstract: Object detection systems are essential tools for identifying and locating objects within images or videos. When integrated into spectacles or wearable devices, these systems provide users with real-time information about objects present in their surroundings. This functionality serves diverse purposes, such as assisting visually impaired individuals in navigating their environment or offering augmented reality data to workers during tasks. Region-based Convolutional Neural Networks (RCNN) represent a prominent machine learning model …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article