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135 articles for “deep learning”
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AI-Integrated Precision Agriculture System for Fertilizer Optimization, Multimodal Crop Yield Prediction
Abstract: Agriculture is rapidly transforming into a data-driven ecosystem supported by advances in artificial intelligence (AI), Internet of Things (IoT) sensor networks, and satellite remote sensing technologies. These innovations enable precision-driven decision-making aimed at improving productivity while minimizing environmental impact. This paper presents an AI-integrated precision agriculture system designed to optimize fertilizer usage and enhance crop yield prediction accuracy through a robust multimodal deep learning framework. The proposed approach integrates heterogeneous …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 1, 2026 · pp. 11–17 Read article
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Recognition and Detection of Content in Video Using OpenCV
Abstract: The emergence and continued reliance on the Internet and related technologies has resulted in massive amounts of data that can be analysed. Humans, on the other hand, do not have the cognitive abilities to comprehend such vast amounts of data. Machine learning (ML) is a mechanism that enables humans to process large amounts of data, gain insights into the data's behaviour, and make more informed decisions based on the analysis's …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 2, 2021 · pp. 42–47 Read article
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A Report on Object Detection and Caption Generator
Abstract: Image Caption Generator is a application that generates captions for images. The image's semantic information is recorded and transformed into plain language. The capture mechanism is a timeconsuming effort that combines picture processing and computer vision. The mechanism must be capable of detecting and establishing links between items, humans, and animals. The goal of this article is to use deep learning to detect, recognize, and generate meaningful captions for a …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 2, 2021 · pp. 13–36 Read article
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Machine Learning-Based Channel Estimation for 5G NR Systems: A Comprehensive Review of TDL/CDL Channel Models and CNN Architectures
Abstract: Accurate channel estimation is a fundamental requirement for reliable communications in fifth-generation New Radio (5G NR) systems, where highly dynamic propagation environments impose severe challenges on conventional pilot-based methods. This study provides a thorough analysis of channel estimate methods for 5G NR, including everything from contemporary deep learning (DL) techniques based on Convolutional Neural Networks (CNNs) to traditional Least Squares (LS) and Minimum Mean Square Error (MMSE) estimators. Our analysis …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Comparison of Various Methodologies used for Automating Plant Disease Detection using Image Processing
Abstract: In India, major of economy and development depends on agriculture, so plant disease detection becomeimportant for us so that if any crop is destroyed due to diseases is known to us prior and we can overcomethe loss of crops due to plant diseases. It is better to catch the disease in the initial phase so that the largescaledamage of crops can be prevented. Traditionally, the diseases incurred via the naked …
Published in International Journal of Agrochemistry · Vol. 7, Issue 1, 2021 · pp. 20–23 Read article
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Region-based Object Detection and Classification using Faster R-CNN
Abstract: With the advent of Deep Learning the machine learning systems are able to recognize and classify objects of interest in an image. Various advancement has been done in the field of object recognition and classification. Our research work focusses on improving the R-CNN, Fast R-CNN, YOLO architecture. The work focused on using Region Proposals Network (RPN) to extract region of interest in an image. RPN outputs an image based on …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 6, Issue 2, 2020 · pp. 22–30 Read article
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AI-Based Fraud Detection in Financial Transactions
Abstract: Financial fraud continues to pose a severe danger to individuals, businesses, and the global economy, necessitating the development of effective and innovative detection and prevention approaches. This research study examines the use of artificial intelligence (AI) techniques to detect fraudulent conduct in financial transactions. This paper investigates the advancements, challenges, and courses of AI-based fraud detection in financial transactions through a thorough examination of the research, case studies, and practical …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 1–9 Read article
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Exploration of Explainable Artificial Intelligence (XAI) Techniques to Enhance Model Interpretability
Abstract: Explainable Artificial Intelligence (XAI) has become a major research field because of the rising application of complex machine learning and deep learning models in actual decision-making systems. Although such models are accurate, they are in many cases black boxes and therefore the users do not have much understanding of the way the decisions are generated. This absence of transparency brings up some serious concerns connected with trust, accountability, fairness, and …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Semantic Segmentation for Object Detection in Videos using Mask RCNN
Abstract: The segmentation of object instances is an essential step in real-time video detection. Object detection is the problem of detecting the information of all types of items in an image by designating their location with a rectangular box. Using its remarkable feature-learning capabilities, deep learning promotes object detection research. Numerous researchers have utilised various machine learning algorithms for object detection and have focused on enhancing the accuracy of feature extraction. …
Published in International Journal of Digital Communication and Analog Signals · Vol. 8, Issue 2, 2022 · pp. 7–15 Read article
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A Machine Learning Framework for Fake News Detection Using Embeddings and Dimensionality Reduction
Abstract: The broad sharing of information throughout human history was greatly accelerated by the emergence of the World Wide Web and the swift rise of social networking platforms such as Facebook and Twitter. Due to the extensive use of social media, users now generate and distribute vast amounts of content at an unprecedented rate, and a portion of this information is inaccurate or detached from factual reality. Automatically classifying a written …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 · pp. 8–14 Read article
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Convolution Neural Network Model to Classify Photo Gallery on an Android Device
Abstract: The classification of images is a classic topic in the domains of image processing, computer vision, and machine learning. Convolution Neural Networks, a sort of deep learning that falls under the Machine Learning sub-domain, have been used in this model. This model was inspired by the problem that students experience at the end of the academic year is that their phones become cluttered with photos from various sources. The aim …
Published in International Journal of Analog Integrated Circuits · Vol. 8, Issue 1, 2022 · pp. 9–17 Read article
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Combating Deepfakes and AI-Generated Misinformation: Towards a Digital Likeness and Integrity Framework for India
Abstract: The real struggle is to distinguish what is real and what is fake in the communication of the hyper-digitalized age, in which AI and generative technologies significantly impact the field of communication. The change in the creation and consumption of information has come with the deepfake AI-generated fake media that can imitate a human in voice, image, and video. However, on the one hand, generative models such as Generative Adversarial …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 1, 2026 · pp. 1–20 Read article
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Advancing Early Detection of Menkes Disease Through Image Analysis and Biosensor Integration
Abstract: Menkes disease, a rare X-linked recessive disorder of copper metabolism, poses significant challenges in early diagnosis due to its nonspecific initial symptoms. This paper presents a comprehensive approach to enhance the early detection of Menkes disease by leveraging image processing techniques, pattern recognition algorithms, and innovative biosensor technologies. A novel framework is proposed that combines analysis of hair microscopy images, facial feature recognition, and copper-sensitive biosensors to create a multi-modal …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 24–34 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Blind Assistance System using Tensorflow
Abstract: Because of item recognition's cozy relationship with video investigation and picture understanding, it has drawn in much exploration consideration lately. Customary item discovery techniques are based on carefully assembled highlights and shallow teachable designs. Their exhibition effectively deteriorates by building complex outfits which join numerous low-level picture highlights with undeniable level setting from object finders and scene classifiers. With the fast improvement in profound learning, all the more amazing assets, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 1, 2021 · pp. 6–12 Read article
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Use of Natural Language Processing for Hate Speech Detection on SocialMedia:
Abstract: The exponential growth of social media platforms has led to an increase in user- generated content, enhancing global connectivity but also facilitating the spread of harmful language, including hate speech. Addressing this issue requires robust, Naïve Bayes, Decision Tree, K-Nearest Neighbours (KNN), Linear Regression, and Random Forest—were tested, with Linear Regression achieving the highest accuracy automated systems for detecting and mitigating offensive content. This paper presents a comprehensive analysis of …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 · pp. 9–16 Read article
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Privacy Policy Summarization and Detection of Unfair Clauses
Abstract: ABSTRACTLess than 1% of all users read the privacy policies (or terms and conditions) that accompany software products. This can be attributed to their low level of readability, length, and complexity. Hence, this allows corporations to sneak in clauses which may compromise a user’s privacy, allowing them to use their data for monetary benefit. For example, corporations may sell user data to third parties for targeted advertising. To tackle this, …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 1, 2020 · pp. 35–41 Read article
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An Overview on AI in Thermal Behaviour of Polymers
Abstract: The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the thermalanalysis of polymers and composite materials has transitioned from experimental curiosity to acornerstone of material science. By replacing costly and time-consuming trial-and-errorlaboratory testing with predictive modeling, AI is accelerating the development of advancedthermal interface materials, fire-retardant polymers, and aerospace-grade composites. Theprediction and optimization of the thermal behavior of polymers and composite materialsrepresent a cornerstone of modern materials science, …
Published in International Journal of Composite and Constituent Materials · Vol. 12, Issue 1, 2026 · pp. 12–16 Read article
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CyberSentinel: A Proposed Hybrid AI Framework for Real-Time Cyber Threat Intelligence
Abstract: Modern cyberattacks have grown far more sophisticated, frequent, and fast-moving than the signature-based intrusion detection systems many organizations still rely on. This paper proposes CyberSentinel, a hybrid artificial intelligence framework for real-time cyber threat intelligence (CTI) that combines three complementary techniques into a single detection pipeline: a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) module for network traffic anomaly detection, a Random Forest ensemble for structured log classification, and a transformer-based …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article