Search
216 articles for “Features extraction and Detection”
-
Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
-
Detecting Phishing Websites Using Hybrid Methodologies
Abstract: In the digital era, personal information theft has become a widespread and increasingly severe crime. Cybercriminals, often known as hackers, use deceptive strategies, with phishing websites being a major method for stealing confidential data. These fake websites imitate legitimate ones, tricking users into revealing sensitive personal and financial information, which has led to a rise in fraud cases. To address this escalating threat, a comprehensive research paper is proposed. This …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 59–65 Read article
-
Fault Investigation of Rolling Element Bearing using Soft Computing
Abstract: AbstractRolling element bearing is the most significant mechanical component of any rotating machinery and used in vast applications from the surgical machine tool to aircraft etc. In the present research, an experimental investigation has been done using vibration analysis, continuous wavelet transform (CWT), and soft computing, i.e., support vector machine (SVM) and k-nearest neighbor (k-NN) for fault detection and diagnosis of rolling element bearing. Vibration signatures in the time domain …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 8–22 Read article
-
Human Motion Recognition Using Optical Flow Based Particle Filtering
Abstract: ABSTRACTHuman motion recognition has been a significant topic in computer vision due to its numerous applications such as video surveillance, human machine interaction and video retrieval. One core difficulty behind these applications is mechanically identifying low-level actions and high-level activities of concern. This paper presents a technique of automatically identifying the motion accomplished by humans. The speeded up robust features (Optical flow with kinetic energy algorithm) are made use of, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 1–9 Read article
-
Audio-Only Speaker Identification using Principal Component Analysis based Back-Propagation Learning Neural Network in Noisy Environment
Abstract: This paper introduces text dependent speaker identification system on Principal Component Analysis based Back-Propagation learning neural network which deals with detecting a particular speaker from a known populations under noisy environment. For audio pre-processing, ends point detection, silence parts removal, frame segmentation and windowing techniques have been used and wiener filter has been applied to remove the background noise from the audio speech utterances. To reduce the dimension of the …
Published in Current Trends in Signal Processing · Vol. 3, Issue 3, 2013 · pp. 1–10 Read article
-
AI-Based Criminal Identification System A Breakthrough Approach
Abstract: Identifying and locating a perpetrator is a time-consuming and difficult process. The perpetrators are growing more skilled, leaving no biological evidence or fingerprint impressions at the crime scene. Using cutting-edge face recognition technology is a quick and easy solution. Through the use of linear programming, this research presents an innovative approach to classifying all face tracks collectively. In addition to the following, it incorporates: a novel method for extracting more …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 1–14 Read article
-
Natural Language Processing-Based Plagiarism Detector
Abstract: Plagiarism is the act of taking another's work and claiming it as his/her own without giving the credit. Plagiarism is a grave concern in many fields like education, literature, business, etc. The project aims for text and image plagiarism detection employed by a web application containing four modules. Text plagiarism is detected when the input is either text or PDF. For PDF, the text extraction is done from the PDF …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 27–35 Read article
-
Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
-
A Real-time Automated Drowsiness Detection of Driver Using the Visual Behaviour and Machine Learning Technique Through WebCam
Abstract: In our day-to-day life, many accidents can occur due to the drowsiness of the driver. It is one of the causes of road accidents. To prevent accidents, we proposed a system to detect the drowsiness of driver by measuring the eye aspect ratio, mouth yawning and alert the driver. It will save the life of a person. In this, the driver fatigue is continuously captured by webcam. Image processing methods …
Published in Journal of Web Engineering & Technology · Vol. 10, Issue 2, 2023 · pp. 10–19 Read article
-
Investigation of Surface Electromyography Signal for an Upper Limb Amputee
Abstract: Surface electromyography (SEMG) is a method to measure the muscle activity of the skin. Sensors placed on the skin detect the electrical current or signal generated by active muscles. Lot of the research has focuses on the detection of signal from upper limb amputee with activity of triceps and biceps muscles. Our main aim of this study is to process the acquired signal from the different muscles of the shoulder …
Published in Current Trends in Signal Processing · Vol. 7, Issue 1, 2017 · pp. 19–28 Read article
-
A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
-
License Plate Detection and Recognition of Moving Vehicle Using Open CV
Abstract: License plate detection and recognition system is to localize and extract license plate number of moving vehicle in real time environment. The system works on captured video stream of moving vehicle obtained from real working environments. This system is divided into four steps—video acquisition, vehicle detection, license plate detection, and character recognition. Detection of moving objects, i.e., vehicle in video streams is the first relevant step. For vehicle detection, we …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 32–42 Read article
-
Unleashing the Power of Mathematics in Natural Language Processing: Sentiment Analysis Perspectives
Abstract: Sentiment analysis (SA), which utilizes natural language processing (NLP), computational linguistics, text analysis, image processing, and video processing to extract and analyze subjective information from the internet, social media, and other sources, is becoming increasingly popular in both the business world and the scientific community. It is even possible to model it so that it focuses on polarity, sentiments and emotions, urgency, and even goals. It is able to distinguish …
Published in Recent Trends in Programming languages · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
-
Enhancing Explainability in Machine Learning Based Spam Email Detection Using LIME and SHAP
Abstract: Spam emails represent a continual and irritating cybersecurity issue due to the fast expansion of cyberspace communication. These messages are unwanted and, in some cases, dangerous, such as phishing schemes, identity theft, and the propagation of malware. They cause severe financial and data security threats to individuals and organizations. Conventional spam detection techniques, such as rule-based spamming, blacklisting, and keyword classification, are techniques that find it difficult to match adaptive …
Published in Journal Of Network security · Vol. 14, Issue 2, 2026 · pp. 35–48 Read article
-
Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
-
AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
-
An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
-
Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
-
Exploiting Phase of Speech Signal for Speaker Recognition
Abstract: Abstract—Performance of speaker recognition system with feature based on temporal phase is presented in this paper. In the state of the art spectral feature, Mel Frequency Cepstal Coefficient (MFCC) only magnitude of the Fourier Transform of speech signal is considered while phase is ignored. The cepstral coefficients extracted from temporal phase (MFTPC) of speech signal are used as features for speaker recognition system. The performance of MFTPC feature is evaluated …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 81–87 Read article
-
Robustness of Deepfake Detection Systems Against Adversarial Attacks
Abstract: This paper explores a deep learning system to detect deepfake videos, a common type of fake media. With the use of sophisticated methods such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), our system can reliably discern between authentic and altered videos. It analyzes both the images and the audio in videos to find signs of deepfake manipulation. We process video frames and audio, extract features with CNNs …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article