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20 articles for “SVM linear”
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Brain Tumor Detection
Abstract: The MRI, or magnetic resonance imaging, is one of the most common practices in detecting a brain tumor since it contains important information used to extensively scan the human brain’s internal anatomy. The treatment of any tumor depends entirely on the knowledge and expertise of the physician. This paper reflects the identification of brain tumors using different machine learning algorithms along with the convolution neural network (CNN) and transfer learning. …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 8, Issue 1, 2021 · pp. 45–52 Read article
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Stock Price Analysis and Forecasting Using Linear Regression and SVM Classifiers
Abstract: In this study, we attempt to implement a Machine Learning approach to predict stock market prices. Linear Regression is very effectively implemented in forecasting stock prices, returns, and stock modelling. This project is for common users as the prediction is done on all of the companies. We outline the design of the Linear Regression model with its salient features and customizable parameters. We select a certain group of parameters with …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 62–66 Read article
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Fake News Detection Using N-Gram Analysis and Machine Learning Algorithms
Abstract: Fake news is untrue information presented as news. Fake news easily spread than real news amongst social networking sites. Detection of fake news is an important emerging research area which is gaining popularity. The main challenge in fake news detection is limited availability of resources (datasets). This project work detects fake news using n-gram analysis and machine learning algorithms. Evaluation and comparison between two feature extraction technique namely Term Frequency …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 8, Issue 1, 2021 · pp. 33–43 Read article
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User Personality: Prediction and Question Answering System
Abstract: Personality refers to the general traits of a person based on his or her psychological and individual characteristics that reflect into a person’s overall nature and behaviour. Among the featured measures of this system are the MBTI (Myers Briggs Personality Type) which divides individual personalities into 16 distinct types across four axes. To predict the personality of an individual to get a hint about the individual, a personality prediction system …
Published in Journal of Advancements in Robotics · Vol. 10, Issue 1, 2023 · pp. 5–17 Read article
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Predicting Client Behavior for Bank Marketing Using Multi-Layer Perceptron Model
Abstract: AbstractThese days machine learning is one of the most widely used approaches in every industry. And among many techniques of machine learning, classification is the most used one. In this paper, various classification models are used to draw some conclusion for many input variables and one output variable of banking data and classify the output variable into two classes. Various statistics are shown which are generated during classification. The work …
Published in Journal of Advancements in Robotics · Vol. 4, Issue 2, 2017 · pp. 5–8 Read article
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A Novel Approach for Confidence Estimation using Support Vector Machines for More Accurate Value Prediction
Abstract: Data dependencies create hurdles in exploiting instruction-level parallelism (ILP) among instructions. To overcome them, data value predictors are used which guess instructions’ result before it is actually executed. Thus, future instructions which depend on the outcome of that instruction executes sooner. But, since value prediction accuracy is very crucial in determining the amount of parallelism that can be exploited, confidence estimation is used along with it to lessen the value …
Published in Journal of Advancements in Robotics · Vol. 1, Issue 2, 2014 · pp. 18–29 Read article
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Steady State Visual Evoked Potential Based Brain Computer Interface System
Abstract: The steady-state visual evoked potential (SSVEP) is a brain response that can be measured by an electroencephalogram (EEG) when a subject looks at periodic luminance- or contrast-modulated stimuli. In this study, flickering Light Emitting Diode (LED) is used as visual stimulation. Mostly, brain response is recorded using an electroencephalograph (EEG) and recorded in the brain's occipital lobe which is associated with human vision. The study encompasses key stages, beginning with …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 35–43 Read article
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Face Recognition using LDA based Support Vector Machine
Abstract: AbstractRecognition of a person is an easy task for human brains. From different experiments, we have found that even one to three days old babies are able to distinguish between known faces. So, it is very difficult task for a computer to recognize an unknown human face although a computer has been trained with a huge set of human face. Now-a-days face recognition has received significant attention of researchers. Lots …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 2, 2014 · pp. 1–7 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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PSO tuned SVM-SMC Controller for the Trajectory Tracking of a Five Bar Linkage Manipulator System
Abstract: AbstractRemarkable advantages of SVM make it one of the most widespread and successfully used estimating technique of the era especially for the non-linear systems like robotic manipulators. Control system used in trajectory tracking problems of robotic manipulator is of great importance and hence, accuracy in tracking of manipulator is directly associated to the improvement in the quality of the controller engaged. So, to improve the control performance of the SVM …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 46–55 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
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Utilization of Statistical Learning Algorithms for Prediction of Elastic Modulus of Jointed Rock Mass
Abstract: This study uses two statistical learning algorithms for the prediction of elastic modulus (Ej) of jointed rockmass. The first algorithm uses support vector machine (SVM) that is firmly based on the theory of statisticallearning and uses regression technique by introducing -insensitive loss functionhas been adopted. Thesecond algorithm uses relevance vector machine (RVM). It is based on a Bayesian formulation of a linearmodel with an appropriate prior that results in a …
Published in Recent Trends in Civil Engineering & Technology · Vol. 1, Issue 1-3, 2011 · pp. 81–94 Read article
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Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Review Paper on Efficient Quality Inspection of Food Products Using Neural Network Classification
Abstract: AbstractWith the increasing competiveness in the field of food production growing at a faster pace across the globe, quality is one of the most desirable features that a product should possess. The ability to produce quality as well as safety food is the most prerequisite factors for both, national and international market. This paper explains the recently developed approaches and latest research efforts related to the assessment of the quality …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 1, 2017 · pp. 1–14 Read article
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Umpire’s Assistant : DRS with computer vision
Abstract: In any game, a fair decision is necessary to ensure that the game is played fairly. Any bad judgement made due to human error could determine the game's outcome. The literature study mentioned computer vision and image processing algorithms, which were shown using numerous cameras. With the use of a high-quality smartphone camera, this study focuses on a system that assists the umpire in making decisions such as no-ball, LBW …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 1, 2022 · pp. 24–27 Read article
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Improvement of Indirect Vector Control Induction Motor Drive Performance under Low Speed Operation using Five-Level Inverter
Abstract: The dynamic performance of vector controlled induction motor drive is poor and peak motor torque decreases under low speed operation. This reduction in torque is due to the non-linearity of voltage to frequency (Hz) during low frequency operation. The non-linearity is caused by stator voltage drop which in turn requires a larger percentage of overall terminal voltage. To overcome these problems multilevel inverter fed induction motor drive is presented in …
Published in Journal of Power Electronics and Power Systems · Vol. 3, Issue 2, 2013 · pp. 8–15 Read article
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Unsupervised Learning Techniques in Neural Network for Face Recognition
Abstract: This paper represents the review of systematic comparison between of unsupervised learning algorithms for face recognition. In neural network, different algorithms are used for face recognition. Each algorithm has different accuracy factors. Commonly these methods asset a set of base images and serve faces as linear combo of images. In our proposed review, firstly we discuss about the face detection using neural network along with the concept of digital image …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 25–29 Read article
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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