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216 articles for “Features extraction and Detection”
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Automated Vessel Segmentation of Retinal Vessels using Hybrid Region Information
Abstract: AbstractRecent researches state that the categorization of retinal vessels into artery/vein (A/V) is a critical phase for automating the detection of vascular adjustments and for the calculation of function symptoms related to numerous systemic illnesses which includes diabetes, high blood pressure, and different cardiovascular situations. This paper affords an automatic method for A/V class, primarily based on the evaluation of a graph extracted from the retinal vasculature. The proposed method …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 28–36 Read article
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Image-Based Evaluation of Implant Tissue Interface Integrity in Polymer Orthopaedic Devices
Abstract: Polymer orthopedic implants offer radiolucency and mechanical compatibility with bone, but long-term success depends on maintaining a stable implant–tissue interface. Routine imaging is widely available for follow-up, yet interface integrity is commonly judged qualitatively, limiting early detection of fixation compromise and reducing comparability across devices and time points. This work presents an image-based methodology to quantify interface integrity by extracting interpretable interface descriptors from a standardized interface belt around the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 170–179 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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Bearing Defect Diagnosis: An Approach for Manufacturing Industries Using Wavelet Transform Based Features
Abstract: To maintain reliability in the manufacturing units, industries have concentrated their attention on the condition based maintenance. Fault detection and diagnosis are the two of three condition based maintenance mainstays. Bearing is one of the most important and essential components of the rotating machines. Hence, the researchers have shown their interest in bearing fault detection and diagnosis from the last few years. They mainly use bearing vibration as fault characteristics …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 15–21 Read article
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Breast Cancer Detection Using Deep Learning
Abstract: Breast cancer, according to the Breast Cancer Institute, is one of the most difficult kinds of cancer that is extremely threatfulfor women all over the world. Early cancer discovery, followed by appropriate treatment, can help minimize the risk of deaths in the first stage of respective cancer only and increase the likelihood of survival by up to 8%. Medical imaging research has become increasingly reliant on machine learning and deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 1, 2022 · pp. 33–42 Read article
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Hyperspectral Image Compression and Classification: A Survey
Abstract: The applications of hyperspectral images (HSI) are many, which include agriculture, food quality, remote sensing, medical diagnostics and safety assessment. Hyperspectral image analysis has been used for detecting contaminants and identifying defects in food. It also utilizes advanced software and hardware tools hence allowing users to diagnose and detect pathologies. In this paper an avant-garde investigation about Hyperspectral image compression and classification techniques which can be used in various applications …
Published in Journal of Remote Sensing & GIS · Vol. 13, Issue 4, 2022 · pp. 9–23 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Flood Inundation Mapping for using Sentinel-1 SAR Data for Assam during 2018
Abstract: This paper is focusing on the flood inundation mapping of Hailakandi, Assam flood during 2018 using Sentinel 1 Single Look Complex (SLC) and Ground Range Detected (GRD) data. For the analysis of water pixels, pre and post event images of SLC and GRD data were downloaded with similar specification such as same date, pat and row. Supervised classification is performed with the pre and post event of the study area …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 8, Issue 2, 2019 · pp. 16–25 Read article
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Review on CBIR Image Based on Colour, Texture and Shape Features of Biomedical Image Applications
Abstract: This study seeks to understand how different image enhancing methods affect the sensitivity of contrast-based textural measures and morphological traits derived from high-resolution satellite data (three-band SPOT-5). The built-up/non-built-up detection framework is the backbone of every biomedical application. Using supervised learning while working with a low-resolution reference layer reduces uncertainty and boosts the reference layer's quality in a roundabout way. The image's histogram is recalculated based on contrast in order …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 8–13 Read article
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Bearing Fault Diagnosis Using ANN and SVM with the Help of Wavelet Transform Based Features
Abstract: Many researchers use vibration signals as fault characteristics of any rotating bearing for fault detection and use various optimization techniques available for fault of bearing classification. The method of fault classification uses few neural network (NN) geometry and parameters necessary for the formulation. There is no derived formulation which can be used to select the optimal values for the network parameters. The parameters which are required to be calculated, impacts …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 2, 2017 · pp. 26–34 Read article
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Urban Flood Hazard Modeling for Noida City
Abstract: This contemporary work unveils the usage of a new methodology to carry out an accurate hazard mapping of urban flood footprints. It is based on wetness transformation. It is a procedure of conversion of multi-spectral-bands into three dimensional feature space. The present study embraces conversion of thematic mapper (TM) imagery of Landsat to a three dimensional array; brightness, wetness and greenness, followed by the technique of change detection to locate …
Published in Journal of Remote Sensing & GIS · Vol. 7, Issue 1, 2016 · pp. 10–26 Read article
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Sustainable and Smart Solutions Utilizing Feature Descriptors Analysis
Abstract: Neighborhood highlight locators and descriptors (hereinafter extractors) play a key part within the cutting-edge computer vision for developing smart solutions. Their scope is to extricate, from any picture, a set of discriminative designs (hereinafter key points) show on a few parts of foundation and/or closer view components of the picture itself. A prerequisite of a wide run of down to earth applications (e.g., vehicle following, individual re-identification) is the plan …
Published in Journal of Electronic Design Technology · Vol. 13, Issue 3, 2022 · pp. 35–40 Read article
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A Profound Analysis on Complex Multiclass BCI Signals Classification by an EEG Device
Abstract: With a major shift in the technology paradigm today in the area of deep learning and artificial intelligence, one of its important applications today is found in brain-computer interface (BCI). Brain computer-interface, also known as neural control interface or mind-machine interface is a device that helps a user to interact with a computer using only his brain-activity, which is measured usually by Electroencephalography (EEG). The usage of such mechanism has …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 8, Issue 1, 2021 · pp. 22–44 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 15–27 Read article