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1474 articles for “learning”
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A Survey of Seasonal-based Movie Recommendations Using Machine Learning Through a Hybrid Approach with User Interest in Various OTT Platforms
Abstract: No matter their age, gender, race, color, or region, everyone enjoys watching films particularly during festival season. We are all, in the most basic sense, connected to one another through this beautiful medium, but what really grabs attention is the fact that, regardless of how unique our choices and combinations are in terms of picture show preference, one thing remains constant. Certain people have a preference for certain types of …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 24–29 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Sentiment Analysis of X (Formerly Twitter) Using Machine Learning
Abstract: Sentiment analysis is a methodology to determine the nature and behavior of each and every user for the content posted on the social media platform in the form of post and feed. Consumers of the online platform are encouraged to post reviews of the product that they purchase. Little attempt is created by Amazon to confine or limit the content of these reviews. The number of reviews for various merchandise …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 28–37 Read article
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House Price Prediction Using Linear Regression In Machine Learning
Abstract: In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people's high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 92–100 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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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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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Bank Locker Security System Using Machine Learning
Abstract: The Bank Locker Security System integrates cutting-edge technology solutions to strengthen the security of bank locker facilities. This system uses biometric identification techniques, such as facial recognition and fingerprint scanning, to confirm users' identities before granting them access to the lockers. Furthermore, access control techniques based on RFID technology are employed to augment security protocols. The locker area is equipped with real-time monitoring and alerting tools that enable fast detection …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 16–20 Read article
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DentiDetect: Dental Diagnosis Powered by Deep Learning
Abstract: Dental X-rays play a crucial role in modern dentistry, enabling dentists to detect cavities, bone loss, and other hidden dental issues that are not easily visible during a routine examination. X-rays offer a clear picture of teeth, bones, and nearby tissues, enabling early identification of issues. This helps create more efficient treatment strategies and improves patient outcomes. Three commonly used types of X-rays include bitewing, periapical, and panoramic. Bitewing X-rays …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 3, 2024 · pp. 21–26 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 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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Utilizing Machine Learning for Waste Analysis
Abstract: The Internet of Things can be expanded to include any physical object with an IP address that allows data to be transmitted over a network by installing electronic devices such as networking hardware, sensors, and software. The Internet of Things (IoT) offers enhanced connectivity for an array of devices, services, protocols, and applications. It is further defined by its diverse nature. Not just in houses and smart cities has IoT …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Deep Learning Approach to Produce Artificial Speech (Text-To-Audio)
Abstract: This program utilizes key features of the .NET framework to facilitate smooth text-to-speech conversion and audio playback. Upon execution, users are prompted to input text via a graphical user interface (GUI), which the program converts into speech using the ‘SpeechSynthesizer’ class from the ‘System. Speech.Synthesis’ namespace. The audio that has been synthesized is handled and stored as a WAV file called ‘output.wav’ by utilizing the ‘FileStream’ class, allowing for future …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 28–33 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 Read article
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Cloud Enabled Machine Learning Framework for Medicine System
Abstract: The Medicine Generic App is a cutting-edge mobile application designed to empower users with information about generic medications. Given the rising expenses of healthcare and prescription medications, this app acts as a useful resource for consumers to make informed decisions regarding their medication options. The Medicine Generic App aims to promote generic drug usage, reduce healthcare costs, and improve medication management for users. By providing detailed information and price transparency, …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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Smart Environmental Noise Monitoring System Using IoT and Machine Learning for Urban Pollution Control
Abstract: Human race has steadily evolved over past centuries. Development of new technology, vigorous research, consistent efforts, indomitable will to find solutions for the problems, are the key factors to shape our future in way that everyone gets safe, secure and satisfactory life. Construction industries provides basic but most valuable service or product or we can say that construction industries fulfill the basic needs of individual and group of people by …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article