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798 articles for “deep learning”
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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 Read article
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Intelligent Paradigms in Subsea Connectivity: A Comprehensive Review of Artificial Intelligence in Underwater Communications
Abstract: Underwater wireless communication (UWC) plays a critical role in ocean exploration, environmental monitoring, offshore energy operations, disaster management, and naval defense. However, the underwater environment presents significant communication challenges, including severe signal attenuation, multipath propagation, Doppler effects, limited bandwidth, high latency, and energy constraints. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have emerged as promising solutions to address these limitations and enhance the efficiency, reliability, and adaptability …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Traffic Density Estimation Using Image Frames in Python
Abstract: Traffic congestion is a critical challenge in modern urban environments, leading to significant delays, environmental pollution, and increased accident rates. With the rapid growth of vehicle populations in metropolitan areas worldwide, the need for intelligent and automated traffic monitoring systems has become increasingly urgent. Traditional monitoring approaches, such as inductive loop detectors and manual surveillance, are limited in scalability, deployment cost, and adaptability to dynamic traffic scenarios. This paper presents …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 38–45 Read article
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Enhancing Cybercrime Detection Through Big Data Analytics: A Conceptual Framework
Abstract: The growing complexity of cybercrime reduction and prevention difficulties necessitates a different approach to dealing with the massive amounts of data involved. The issues of reducing and preventing cybercrime are becoming more complex as cybercrime becomes ingrained in our daily lives. When it comes to showcasing the original division of criminal activities, traditional police operations typically fall short, which means they contribute less to the right deployment of police resources. …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 1–11 Read article
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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FACE EMOTION RECOGNITION TO DETECT DEPRESSION
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
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Energy-efficient Image Classification on Edge Devices: Implementation and Evaluation
Abstract: Image classification is a computer vision problem where an algorithm determines a class or label for a given image. Various real-time applications like object recognition, medical diagnosis, person recognition, etc. Image classification property on edge devices is useful for autonomous vehicles, surveillance, and healthcare and internet of things deployments. The advancement of deep learning based methods and graphics processing units (GPU) devices allows efficient processing locally. The study utilizes a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 10–18 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article
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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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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article
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Evolving Perspectives: Innovations in Object Detection and Identification
Abstract: One of the most important developments in computer vision has been the creation of object detection and identification systems, which have allowed robots to perceive and understand visual data similarly to humans. These systems locate each object by drawing a bounding box around it, in addition to detecting and classifying every object in an image or video. This study suggests a novel method for item identification and detection that makes …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 3, 2023 · pp. 23–27 Read article
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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JATAYU: A Stereo Vision–Based UAV for Autonomous Navigation and Human Following in GPS-Denied Environments
Abstract: Traditional unmanned aerial vehicle (UAV) systems primarily rely on Global Positioning System (GPS)-based navigation and conventional computer vision techniques. However, these approaches face significant challenges in GPS-denied environments, such as dense urban areas, indoor spaces, and disaster-affected regions where GPS signals may be weak, unavailable, or unreliable. In addition, limitations in real-time processing, object detection accuracy, and environmental perception can reduce UAV effectiveness in dynamic and unpredictable situations. This paper …
Published in International Journal on Drones · Vol. 2, Issue 2, 2026 · pp. 30–38 Read article
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Artificial Intelligence Techniques for Air-Interface Optimizations and Future Research Directions in 6G Networks
Abstract: This paper is the second instalment of a two-part review on artificial intelligence (AI) for sixth-generation (6G) wireless networks. Where the companion paper traced the generational evolution of mobile networks and the Digital Twin architecture that underpins 6G, this paper narrows the focus to the specific AI techniques expected to drive 6G's autonomous operation and to the air-interface problems those techniques are being asked to solve. We review machine learning, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 · pp. 50–57 Read article
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Convolution Neural Network Model for Intrusion Detection in Network
Abstract: The evolution of the internet has made protecting information a necessity. Network intrusion and prevention plays an integral role in network-based security. The Intrusion technologies primarily used in today’s world deploy various machine learning algorithms and train models based on them resulting in effectively low detection rates. A technical advancement from machine learning, Deep Learning employs complex mechanisms to extract features from samples. As observed that conventional intrusion detection systems …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 7–13 Read article
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Flying Faces: An Automated Recognition System using Raspberry Pi and Drone
Abstract: Facial recognition technology has gained populari- ty in recent years and is used in various applications, such as security and surveillance. However, traditional facial recogni- tion systems are limited in their ability to capture images from different angles and perspectives. In this paper, facial recogni- tion system is presented that utilizes drone technology to cap- ture images from multiple angles for better accuracy. The sys- tem consists of a Raspberry …
Published in Journal of Mechatronics and Automation · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
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A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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NLP Revolution in Education Feedback Analysis: Trends and Challenges
Abstract: Artificial Intelligence (AI) is a rapidly growing area of study in many domains like research and business. Various subsets of AI, such as Machine Learning, Deep Learning, and Natural Language Processing (NLP), are employed to address diverse aspects of data processing and modeling. This review is about the impact of AI on the education system and students feedback for the analysis is required for the enhancement of the technology used …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 21–25 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