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1949 articles for “class” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Soil Analysis Mechanisms for Smart Agriculture-A Review
Abstract: Agriculture, Horticulture, as the single biggest client of freshwater on a worldwide premise and as a significant reason for corruption of surface and groundwater assets through disintegration and synthetic overflow, has cause to be worried about the worldwide ramifications of water quality. The related agro food preparing industry is likewise a huge wellspring of natural contamination in many nations. Hydroponics is currently perceived as a significant issue in freshwater, estuarine …
Published in Recent Trends in Sensor Research & Technology · Vol. 8, Issue 3, 2021 · pp. 6–10 Read article
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Smart Home Automation System
Abstract: Computerization is becoming famous step by step because of various benefits. Till now the current advancement shows that the mechanization framework is overseen by messages, or a few different applications. This study gives a thought of involving IoT for observing and controlling home machines by means of the World Wide Web through remote medium or Wi-Fi. The thought given in this study targets controlling home machines through detecting the movement …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 1, 2022 · pp. 9–23 Read article
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An Evaluation of Letrozole and Clomiphene Citrate Efficacy as Ovulation Induction Medication in Females with Polycystic Ovarian Condition
Abstract: Polycystic ovarian condition is the most common endocrinopathy in anovulatory infertile females. As a long-established conventional treatment for ovulation induction, clomifene citrate (also known as clomiphene) is still recommended to PCOS patients as their first line of treatment. Indian PCOS women are more prone to have high levels of clomiphene resistance due to the high frequency of insulin resistance . While letrozole has a high potential for ovulation induction, it …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 12, Issue 2, 2024 · pp. 23–29 Read article
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Hybrid approach for emotion detection in text using spatial-temporal features
Abstract: In recent years, the incredible exploratory growth of online data in social media mainly Twitter has to lead to growing attention of researchers towards Affective analysis of social media streams. Around 500 million tweets are generated per day all around the globe. Classification of these tweets into different affective classes is an arduous task. We propose a novel approach of classifying a tweet into Ekman’s six basic emotion classes using …
Published in Journal of Advancements in Robotics · Vol. 5, Issue 1, 2018 · pp. 34–44 Read article
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Automatic Chalk Dust Collector
Abstract: AbstractTeaching and learning in schools and colleges are done over the years by writing on boards. This project involves the design and construction of an automatic chalk dust collector by using vacuum technology. Cleaning the board using a duster increases the chalk dust particles in the classroom atmosphere. When concentration level of the chalk dust suspension exceeds a safe limit, occupants of the classroom, especially the teacher are exposed to …
Published in Journal of Open Source Developments · Vol. 6, Issue 2, 2019 · pp. 1–5 Read article
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Human Age and Gender Determination by Using Fingerprints
Abstract: We present a review of technologies to determine human age and gender using fingerprints. Broadly, two methodologies are reviewed, i.e., ridge based human age and gender determination and Image based human age and gender determination. Ridge based technique uses ridge information with its variant statistics measures for classification of a human fingerprint into different classes of age groups and male/female distinction. These methods do not involve separate classifiers for classification …
Published in Journal of Advancements in Robotics · Vol. 9, Issue 2, 2022 · pp. 16–26 Read article
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Automatic Fake News Detection: A Review
Abstract: Misinformation has exploded in the last two decades with the development of digital technologies. The damage caused by it to social harmony, peace, social trust, justice, and democracy has increased the necessity of automatic identification of bogus news and intervention. As more and more content is being available, a person may not deliver much attention to a news piece and may assume it to be reliable just from reading headlines. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 1, 2023 · pp. 29–35 Read article
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Knowledge-based, Automated Land Use/Land Cover Mapping Using Resourcesat-1 AWiFS
Abstract: The availability of large quantity of data from high-resolution space-based sensors along with the existing archives surpassed our ability to extract information from all the data using supervised image analysis techniques. Hence there is a need for automated image classifier with high throughput. Knowledge-based, modular, hierarchical decision-based classifier suitable for the analysis and extraction of major land use/land cover classes from IRS Resourcesat AWiFS data has been developed and the …
Published in Journal of Remote Sensing & GIS · Vol. 3, Issue 1, 2012 · pp. 11–20 Read article
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Detection of Breast Cancer with Python
Abstract: Global cancer data confirms more than 2 million women diagnosed with breast cancer each year reflecting majority of new cancer cases and related deaths, making it significant public health concern. But fortunately, it is also the curable cancer in its early stage. Early diagnosis of breast cancer with timely and effective treatment services improves the prognosis and survival of patients. During classifying tumors, there are significant chances of error and …
Published in Research & Reviews : Journal of Statistics · Vol. 9, Issue 3, 2020 · pp. 5–22 Read article
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Revolutionizing Knee Osteoarthritis Diagnosis: Unleashing the Potential of Vision Transformers
Abstract: Osteoarthritis (OA) is the most common kind of arthritis. By analysing data from both sides of the knee joints, radiologists use the Kellgren–Lawrence (KL) grading system to determine the severity of osteoarthritis (OA). The need for knee arthroplasties has increased as a result of this. Recently, there have been proposals for computer-assisted techniques to improve the precision of OA diagnosis. Choosing between conservative and surgical treatment options for knee osteoarthritis …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 1, 2024 · pp. 24–31 Read article
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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X-Ray Insight: Deep Learning-Enhanced Detection and Grading of Knee Osteoarthritis
Abstract: Osteoarthritis (OA) is the most prevalent form of arthritis affecting the knee. It is a degenerative joint disease characterized by the gradual deterioration of cartilage, typically impacting individuals aged 50 and above, although it can also occur in younger people. The condition progresses slowly, with symptoms intensifying over time, leading to significant pain and discomfort. Early diagnosis and intervention can significantly alleviate pain and enhance the quality of life for …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article
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Real-time DDoS Attack Prediction in SDN Environments Using Machine Learning
Abstract: The ever-growing reliance on sdn-based services necessitates robust security measures against Distributed Denial-of-Service (DDoS) attacks that threaten service availability. This project investigates the development of a real-time prediction system for DDoS attacks in sdn environments, leveraging the power of machine learning. The proposed system employs a Decision Tree classification algorithm implemented in Python. To ensure accurate attack identification, the system meticulously addresses data preprocessing challenges inherent in network traffic datasets. …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 16–27 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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The Role of Symmetry in Topological Insulators and Superconductors
Abstract: Topological insulators and superconductors constitute a class of quantum materials characterized by insulating bulks and symmetry-protected conducting boundaries. Symmetry principles, notably time-reversal (TRS), particle-hole (PHS), and chiral symmetry, play a fundamental role in determining the topological phases and their classification within the Altland-Zirnbauer scheme. TRS protects gapless surface states in topological insulators, while PHS stabilizes Majorana modes in topological superconductors. Symmetry-protected topology extends this framework by considering partial symmetry breaking, …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 01–05 Read article