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10 articles for “data augmentation”
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Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model
Abstract: Diabetic retinopathy (DR) is a leading cause of blindness worldwide, impacting the largest number of individuals who have diabetes. Early identification of diabetic retinopathy may help to prevent severe effects; however, the very limited availability of labeled datasets, and the possibility of overfitting of the model, presents obstacles to obtaining an accurate diagnosis. In this research, a hybrid deep learning strategy is introduced, where Generative Adversarial Networks (GANs) are used …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article
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Deep Learning with CNNs: A Survey of Techniques and Real-World Applications
Abstract: Convolutional Neural Networks (CNNs) have emerged one of the most powerfully used tools in deep learning, particularly in image and pattern recognition tasks. CNNs are being revolutionized through deep learning resulting in a dominant architecture in computer vision as well as other various domains. This paper provides a comprehensive survey of CNN-based deep learning, its methodologies, regularizations, and computational efficiencies. We also address the challenges and future directions of CNN. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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AI-Based Image Detection of Rice Crop Diseases Using Deep Learning and Grad-CAM
Abstract: The Indian economy relies heavily on agriculture, and rice is one of the most significant staple crops grown in the country. Nevertheless, rice cultivation faces numerous challenges due to several leaf diseases, such as bacterial leaf blight, brown spot, and leaf smut. These diseases can lead to substantial yield losses and financial burdens for farmers. Therefore, the early detection and classification of these diseases are essential to minimize crop damage …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 Read article
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Hybrid Machine Learning and Deep Learning approach for Adaptive congestion control in 5G/6G Network
Abstract: The rapid growth of data traffic, fueled by emerging applications such as autonomous systems, augmented reality (AR), virtual reality (VR), and the Internet of Things (IoT), poses major challenges for modern communication networks. With the rollout of 5G and the continuous transition to 6G, sophisticated congestion control techniques are needed to satisfy the demanding requirements of massive machine-type communication (mMTC), ultra-reliable low-latency communication (URLLC), and improved mobile broadband (eMBB). Conventional …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 2, 2025 · pp. 1–8 Read article
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Comparison Analysis of Lumpy Skin Disease Detection System Using X-Ray Images of Animals with the Help of Deep Learning
Abstract: Lumpy Skin Disease (LSD), caused by the Capripoxvirus, is a highly contagious viral infection impacting cattle and other livestock, resulting in significant economic losses due to decreased productivity and mortality. Early detection is critical to mitigate its spread and reduce its impact on agriculture and dairy sectors. This study investigates the efficacy of deep learning methodologies for detecting LSD through X-ray images, offering a non-invasive diagnostic approach to identify internal …
Published in International Journal of Animal Biotechnology and Applications · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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IoT-Powered Weather Monitoring and Irrigation Automation: Transforming Modern Farming Practices
Abstract: It is proposing an IoT-based weather monitoring system. This will monitor, in real-time, the critical environmental parameters aid for farming. Soil moisture, temperature, humidity, and rainfall will be measured parameters that help optimize agricultural practices and perfect the use of water. The IoT technology will, therefore, include a microcontroller such as NodeMCU that tracks soil moisture levels and automates irrigation. If the soil moisture falls below 50%, then the programming …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Customer preferences in adopting AI in their building designs: A Perspective case study from Saudi Arabian architects
Abstract: Recent AI advances have improved Saudi building design inventiveness, efficiency, and cultural sensitivity. Automating tedious activities like image resizing and layout optimization with AI helps designers focus on novel concepts. AI may assess client preferences and society conventions to assist designers adapt their ideas to local cultural values, making architectural development projects more appealing. Even though it has many advantages, artificial intelligence in architecture is confronted with several challenges. The …
Published in International Journal of Architecture and Infrastructure Planning · Vol. 10, Issue 2, 2024 · pp. 25–40 Read article
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Speech Emotion Recognition using Multi- Kernel CNN for Features extraction and Random Forest Classifier
Abstract: Identifying human emotional states from speech signals is the main goal of Speech Emotion Recognition (SER), which has grown to be a significant area of study in affective computing. However, class imbalance and efficient feature extraction from speech data pose problems for many of the current methods. This study suggests a hybrid framework that combines a Random Forest (RF) classifier with a multi-kernel Convolutional Neural Network (CNN) to address these …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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Hybrid Signal Processing Framework for Seamless Integration of Analog and Digital Communication Systems in 6G Networks
Abstract: The next 6G phase of evolution of the communication system is expected to deliver data speedexceeding terabits per second, very low latency, and connectivity everywhere among heterogeneous devices. These performance goals can only be met through signal processing architecture paradigm shift. The paper will describe a Hybrid Signal Processing Framework (HSPF) which combines the analog and digital communication methods to leverage the complementary benefits of the two spheres. The framework …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 · pp. 28–42 Read article
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Hybrid Signal Processing Framework for Seamless Integration of Analog and Digital Communication Systems in 6G Networks
Abstract: The next 6G phase of evolution of the communication system is expected to deliver data speed exceeding terabits per second, very low latency, and connectivity everywhere among heterogeneous devices. These performance goals can only be met through signal processing architecture paradigm shift. The paper will describe a Hybrid Signal Processing Framework (HSPF) which combines the analog and digital communication methods to leverage the complementary benefits of the two spheres. The …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 Read article