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216 articles for “Features extraction and Detection”
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Artificial Intelligence Based Plant Disease Detection
Abstract: This paper analyses the advanced Neural Network (NN) techniques for hyperspectral data processing, with a particular focus on detecting plant disease. To initiate, we will discuss the NN mechanism, types, models, and classifiers that are used to process the hyperspectral data using different algorithms. Following that, this project discusses the current state of imaging and non-imaging hyperspectral data for early screening and diagnosis of Disease. The NN-hyperspectral hybridization method has …
Published in Recent Trends in Programming languages · Vol. 8, Issue 3, 2021 · pp. 11–24 Read article
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Pedestrian Gait Parameter Measurement Using a Cascade of Edge and Corner Detection Technique
Abstract: ABSTRACTMost modern surveillance systems currently rely upon Closed Circuit TV feeds monitoring system. This report documents a new approach towards automating pedestrian recognition within typical video footage. The proposed work shows how the gait parameters can be measured from the video footage using the mathematical theory of Geometry and computer vision and pattern recognition technique which can be further used for recognize individuals. When people walk normal to the viewing …
Published in Journal of Computer Technology & Applications · Vol. 1, Issue 1-3, 2011 · pp. 75–88 Read article
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A Comprehensive Survey on Detection of Video Transitions
Abstract: Video shot boundary detection (SBD) is a fundamental task in the field of video processing and analysis. It plays a critical role in various video applications such as content-based video retrieval, video indexing, editing, summarization, and browsing. Identifying shot boundaries helps segment a continuous video stream into distinct shots, each representing a meaningful visual unit. This segmentation is essential for organizing and interpreting video data efficiently. This study provides an …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 17–26 Read article
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Brain Tumor Detection Using an Artificial Neural Network in MRI Images
Abstract: MRI is the widely used imaging technique in the biomedical field for the detection, diagnosis and evaluation of brain tumors. The large structural variability among brain tumor makes detection of a challenging problem. The medical problems are severe, if the tumor is detected at the later stage. Hence, diagnosis is necessary at the earliest. In this work, a neural network classifier is used for the detection of tumors from the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 5, Issue 1, 2018 · pp. 14–22 Read article
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Emotion Recognition based on Human voice tones
Abstract: In this period of technology and automation, human interaction with machines has become an unavoidable occurrence. Machines are making our lives much easier, stretching their hands wherever it is possible for smoother operation of various tasks. Emotion recognition system is one of the system that can help humans for a much easier and meaningful interaction with machines. It can be used in various branches such as artificial intelligence, health care, …
Published in Current Trends in Information Technology · Vol. 10, Issue 2, 2020 · pp. 1–5 Read article
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Traffic Detection Algorithms Analysis using ML
Abstract: It is difficult to watch traffic on crowded roads. Traffic monitoring procedures are time-consuming, expensive, labor-intensive, and require human operators. The limited accessibility hindered the storing and processing of large-scale video streams. Nonetheless, it is now possible to employe video feeds from traffic monitoring systems for number plate recognition, object tracking, traffic behavior analysis, and surveillance. Static image recognition and vehicle identification in a traffic surveillance system are very useful …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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Enhancing IoT Network Security with Hybrid Deep Learning Classifiers for DDoS Attack Detection
Abstract: The security and operational dependability of Internet of Things (IoT) networks are seriously threatened by the growing susceptibility to Distributed Denial of Service (DDoS) assaults brought about by their rapid expansion. The intricacy and dynamic character of these advanced attacks can provide a challenge to conventional intrusion detection systems. This study presents a novel method for strengthening IoT network security by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Fingerprint Pre-processing and Features Extraction
Abstract: Fingerprint is broadly utilized biometric recognizable proof to distinguish the personality of a man due unwavering quality and adequacy. Identification based on biometric is a well-known technique that recognizes identity of a person. Fingerprint identification system contains pre-processing (PP), features extraction (FE) and matching. In this study, we discussed about pre-processing (PP) and features extraction (FE). The pre-processing steps contain in this study are segmentation, normalization, Gabor filter. The main …
Published in Journal of Advancements in Library Sciences · Vol. 5, Issue 3, 2018 · pp. 40–45 Read article
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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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Brain Tumor Detection Using Image Processing
Abstract: Brain tumor means the aggregation of abnormal cells in some tissues of the brain. Brain tumor can be cancerous or noncancerous. The most common types of brain tumors are Glioma, Meningioma and Pituitary tumor. Early detection of tumor cells is essential in-patient treatment and recovery. A brain tumor is typically diagnosed through a lengthy and complicated process. The MRI images of various patients at various stages can be used for …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 2, 2022 · pp. 8–14 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Face Detection and Recognition System Using Back- Propagation Neural Network Classifier
Abstract: Abstract Today Security is an important part of our everyday lives. Biometric technologies are used for providing and increasing the security of the organizations. Human face recognition is a potential method of biometric authentication. This paper represents a process of face detection and recognition system using principal component analysis with back-propagation neural network. For recognizing the faces there are several steps required. Principal component analysis is used for feature extraction …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 1, Issue 2, 2014 · pp. 19–24 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Face Detection and Recognition Using MTCNN and FaceNet
Abstract: Face detection and face recognition are major tasks in the field of computer vision with several real-world applications and many products being developed in the same field. This study gives a detailed implementation of the product that is developed for accurate detection and recognition of faces along with audio output of the face detected. This development would act as a base for a few future products that can be developed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 132–140 Read article
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Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 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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A Review of Various Deep Learning Models for Classification of BrainTumor
Abstract: Brain Tumor is most challenging and life threading decease now these days. Timely accurately detection of brain tumor is play important role for patient health improvement and it increase life survival rate. Traditional of brain tumor detection relay heavily on manual interpretation of medicalimage, it is very time consuming and chance to human error in detection of brain tumor. Now in recent advancement of Artificial intelligence (AI), Machine learning (ML) …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article