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Real- Time Prediction of Medicinal Herb Plants using Deep Learning 4

Real- Time Prediction of Medicinal Herb Plants using Deep Le...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Sumathy, R. Shalom, R Jehitha Ragul, G. Antony, A Nickson Kit - KalaignarKarunanidhi Institute of Technology Dept of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331523923

Medicinal plants have been important in India's traditional healthcare for centuries, but identifying them can be challenging due to the many different species. This project aims to create a real-time system that recognizes medicinal herb plants using Convolutional Neural Networks (CNN), a type of deep learning that works well for image recognition. The system will be trained on a dataset of herb plant images, using techniques like resizing and data augmentation to improve performance. By doing this, the model will learn to spot even small differences between plant species. We will evaluate the system's effectiveness through accuracy, precision, and recall metrics to ensure reliable identification. By making it easier to identify medicinal plants, this project could help preserve traditional Indian herbal knowledge and encourage the use of these herbs in modern healthcare. In the future, the system will also incorporate real-time prediction capabilities, allowing users to identify herb plants instantly in their natural environments. Additionally, the system could be expanded to include more plant species, contributing to the protection and conservation of medicinal plant biodiversity. © 2025 IEEE.

关键词： Medicinal chemistry

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Preprocessing and Feature Extraction based Deepfake Detection on Combined dataset 2

Preprocessing and Feature Extraction based Deepfake Detectio...

引用

2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Thejas, N.U. Nayak, Hithesh D. Siddique, Abbu Bucker Anas Danish, Mohammed Mamatha, H.R. Pes University Computer Science & Engineering Dept. Bengaluru India

ISBN: (纸本)9798350360523

There are many deepfake detection models available, each with their own limitations. This research concentrates on one such limitation and addresses it. That research gap would be the inefficient behavior of the deepfake detection model on the orientation of faces in the input image or video. The architecture starts by combining the data sets of DFDC, Celeb-DF, and Face Forensics++. Then frame-extraction and pre-processing on the frames take place. The next stage is crucial and differs from other models;it is the feature extraction stage, where specific face-orientation-related features are extracted from each frame. The features that are extracted are a histogram of oriented gradients, local binary patterns, and scale-invariant feature transforms. Later on in the architecture, normalization of features happens in independent neural network pipelines. Then features are combined and passed onto the next neural network, which will classify the videos as deepfake or not. The validation accuracy of this architecture is 95.89%. © 2024 IEEE.

关键词： Feature extraction

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A Hybrid Method for the Detection and Plucking of Mature Coconut Using an Advanced Object Detection Technique 1

A Hybrid Method for the Detection and Plucking of Mature Coc...

引用

1st International Conference on Trends in engineering Systems and Technologies, ICTEST 2024

作者： Muhammed Ilyas, H. Elayidom, Sudheep School of Engineering Cusat Dept. of Computer Science Cochin India

ISBN: (纸本)9798350307795

Vision is a crucial aspect for both artificial intelligence and automated robots. In the case of an automated coconut harvesting machine, a computerized system linked to the machine plays a key role in real-time identification of ripe coconuts within the coconut tree crown. The project employs AI theory to craft an intelligent system. This system utilizes prior knowledge to predict the maturity of coconuts in the current image of the coconut tree crown. A computational board is then employed to compare the captured image with a dataset, enabling the identification of different coconut growth stages and pinpointing the mature coconuts in the current image capture. © 2024 IEEE.

关键词： Object detection

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Hybrid Image Encryption for IoT Applications: Integrating Cellular Automata and Henon Map to Improve Security and Performance 4

Hybrid Image Encryption for IoT Applications: Integrating Ce...

引用

4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Yogi, Biswarup Khan, Ajoy Kumar Roy, Satyabrata Mizoram University Dept. of Computer Engineering Mizoram Aizawl India Manipal University Dept. of Computer Science and Engineering Rajasthan Jaipur India

ISBN: (纸本)9798350387490

Securing the vast volumes of data exchanged over networks is crucial in IoT (Internet of Things) applications. This study introduces an innovative image encryption algorithm that combines the interactive properties of Cellular Automata (CA) and the Henon map to improve both security and performance. CA, renowned for its simplicity and parallelism, are utilized to produce intricate pseudorandom sequences. These sequences are then used as the keystream for encryption purposes. Whereas, the Henon map is employed to incorporate further levels of unpredictability and intricacy into the encryption procedure. The proposed method is thoroughly assessed through considerable experimentation and is compared with existing methodologies. The findings demonstrate substantial enhancements with respect to various standard metrics such as 'Mean Squared Error (MSE)'., 'Peak Signal-to-Noise Ratio (PSNR)'., 'Unified Average Changing Intensity (UACI)'., and 'Number of Pixels Change Rate (NPCR)' measurements., underscoring the resilience and efficacy of the proposed methodology. The results emphasize the capability of this hybrid method to offer a secure and robust performance for image encryption in IoT applications. This method guarantees the integrity and confidentiality of data while outperforming current encryption techniques in performance. © 2024 IEEE.

关键词： Mean square error

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Proposal for a Virtual Reality System to Practice Knife Handling in Cooking 13

Proposal for a Virtual Reality System to Practice Knife Hand...

引用

13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Nakazato, Yukitoshi Kano, Toru Ibaraki Univercity Dept. Computer Science and Engineering Ibaraki Japan

ISBN: (纸本)9798350355079

Knife handling is one of the most important skills in cooking. However, it is difficult to practice the handling of a kitchen knife repeatedly owing to limitations in resources. To address this, we propose a highly realistic system using a haptic device and CT (Computed Tomography) data. This system allows users to practice knife handling in a virtual environment, providing force feedback that reproduces real-life situations. Our goal is to enhance the efficiency and effectiveness of cooking training by enabling unlimited practice without the constraints of ingredients. © 2024 IEEE.

关键词： Virtual environments

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An Ensemble Machine Learning-Based Method to Determine the Presence of Heart Ailment Using Pooled Dataset

An Ensemble Machine Learning-Based Method to Determine the P...

引用

2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Saad, Mirza Nadim Jahan, Esrat Ahmed, Shifat Mohi Uddin, Khandaker Mohammad Southeast University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331529765

Heart disease remains the leading cause of mortality globally, emphasizing the critical need for better diagnostics. This study used a variety of machine learning methods to forecast cardiac disease, using SVM, Random Forest, Decision Tree, KNN, and LGBM. The evaluation measures include accuracy, ROC, precision, recall, and F1 score. Data pretreatment procedures such as cleansing, transformation, integration, and reduction were used to guarantee reliable analysis. The model's performance was further enhanced by hyperparameter tuning. SVM had the lowest performance of the models examined, with 57.23% accuracy, 86% precision, 89% recall, and an F1 score of 87%. The study used three different datasets, combining their strengths to improve model discrimination, decrease overfitting, and increase overall accuracy. We developed multiple models from the combination of RF, DT and LGBM. We found accuracy of up to 99.54% by merging LGBM and Random Forest. These findings illustrate the efficacy of the ensemble approaches and data integration in improving heart disease prediction skills using machine learning. © 2024 IEEE.

关键词： Adversarial machine learning

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Enhancing Network Security with AdvancedNetwork Scanning Tools 6

Enhancing Network Security with AdvancedNetwork Scanning Too...

引用

6th Parul International Conference on engineering and Technology, PICET 2024

作者： Patel, Shubh Christian, Prarthan Mistry, Kartikay Raj, Krenil Raithatha, Hiren Dept. Computer Science and Engineering Parul University Vadodara India

ISBN: (纸本)9798350369748

This research paper introduces a sophisticated network scanning tool designed to enhance cybersecurity measures by integrating advanced techniques in operating system (OS)detection, service scanning, and intrusion detection system (IDS) / intrusion prevention system (IPS) detection. The tool aims to provide a comprehensive approach to network security assessment, offering robust capabilities for identifying potential vulnerabilities and mitigating security risks. The OS detection module employs a combination of fingerprinting techniques and heuristics to accurately identify the underlying operatingsystems of networked devices. This information is crucial forunderstanding the network environment, enabling administrators to implement targeted security measures. The tool incorporatesa sophisticated IDS/IPS detection mechanism to identify and evaluate the effectiveness of intrusion detection and prevention systems in place. This feature is vital for assessing the net- work’s resilience against potential threats and ensuring that the deployed security mechanisms are robust and up-to-date. The research paper details the methodology behind each scanning module, highlighting the innovation and integration of cutting- edge technologies. Additionally, practical use cases and real-world scenarios are presented to demonstrate the tool’s effectiveness in identifying and addressing security concerns in diverse network environments. © 2024 IEEE.

关键词： Network intrusion

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ABC Optimised CNN model for classifying Alzheimer's Disease stages 4

ABC Optimised CNN model for classifying Alzheimer's Disease ...

引用

4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Nagaveni, V. Lalitha Rajeswara Rao, D. Neeharika, S. Vr Siddhartha Engineering College Dept of Computer Science Vijayawada India

ISBN: (纸本)9798350343670

Alzheimer's disease is an advancing neurological illness that affects a significant number of individuals around the globe. Timely and precise identification of Alzheimer's disease is essential to ensure the efficacy of its treatment. Magnetic resonance imaging (MRI) can show structural alterations in the brain, it has become a viable technique for diagnosing Alzheimer's ***, manual MRI examination takes time and is prone to human error. To address these challenges, an algorithm for Alzheimer's Disease detection from brain MRI images using a convolutional neural network is proposed. The primary objective is to create a Convolutional Neural Network (CNN) and fine-tune the hyperparameters using the Artificial Bee Colony Optimization Algorithm. This is pursued in order to categorise the various stages of Alzheimer's disease through analysis of brain MRI images. The convolutional layers are in charge of collecting important characteristics from the images, and pooling layers to condense their spatial dimensions. Later, fully connected layers utilise these extracted features to classify the images accordingly. The goal is to reduce the loss experienced while learning which is a challenging step. When a model produces an output, it contrasts it with the intended output. It then calculates the disparity between the generated and intended outputs, aiming to minimise this difference and approximate the desired output more closely. This is accomplished by adjusting hyperparameters such as learning rate, number of convolution layers, batch size, dropout rate, number of epochs. To increase the model's accuracy, an optimization algorithm performs multiple iterations until a point of convergence. The approach is to develop a CNN model and apply hyperparameter tuning by using the Artificial Bee Colony optimization algorithm, to increase the efficiency of the CNN model. The model's accuracy was enhanced from 86.21% to 94% after applying the Artificial Bee Colony Optimis

关键词： Alzheimer's Disease Artificial Bee Colony Algorithm Convolutional Neural Networks Hyperparameter Tuning Magnetic Resonance Imaging

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Systematic Analysis of Underwater Image Dehazing and Object Detection 6

Systematic Analysis of Underwater Image Dehazing and Object ...

引用

6th Asia Symposium on Image Processing, ASIP 2024

作者： Ghei, Anushka Krishnan, Dhriti Rajesh Santhosh, Gautam Natarajan, S. PES University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350376159

Dehazing underwater images is crucial for several underwater applications, including marine biology, exploration, and monitoring. Because of colour distortion, light attenuation, and scattering, underwater imaging presents particular difficulties. This research presents a systematic survey on using transformers and different Generative Adversarial Networks (GANs) for dehazing underwater photos. This survey study looks into transformer-based models, analyzes GAN designs (CycleGAN, Pix2Pix, and UWGAN) in detail, and compares them using a range of metrics, such as Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM), Frechet Inception Distance (FID), and F1-score. Further analysis was carried out using CLAHE on the best-performing models. Our findings emphasize the benefits and drawbacks of the different designs that were employed as well as prospective directions for further study and advancement. © 2024 IEEE.

关键词： Underwater photography

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Design and Development of a Low-Cost Communication-Based Protection System for Fishermen 1

Design and Development of a Low-Cost Communication-Based Pro...

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1st International Conference on Optimization Techniques for Learning, ICOTL 2023

作者： Sivakumar, S. Arthi, Ts. Premkumar, S. Thillaieaswaran, B. Srm Institute of Science and Technology Dept of Computer Science and Engineering India Galgotia College of Engineering and Technology Dept of Computer Science and Engineering Greater Noida India Galgotias University School of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350328042

Safety and wellbeing of fishermen in maritime environments is of utmost importance. This research seeks to evaluate the feasibility and practicability of an innovative communication-based system designed specifically to protect fisherman. Its main goal is providing an easy, cost-effective solution that improves both safety and communication abilities of these professionals. The system proposed here aims to promote fishers' welfare and safety at its core. It seeks to reduce risks when fishing by employing an infrared-sound wave communication infrastructure that reduces risks while simultaneously increasing efficiency compared to standalone systems. This research investigates scenarios where this combination proves superior. This communication-based system's comprehensive sensor network features both aerial and terrestrial elements. The system seamlessly transfers sensor information, so fishermen have access to vital information that will enhance their situational awareness and facilitate sound decision-making processes. This system employs small sound waves that travel along the surface of the ocean to transmit digital information in binary format as 1s and 0s. They are created by an underwater transmitter emitting ultrasonic signal, effectively creating a communication link between underwater elements and surface ones. This research seeks to address a critical gap in maritime security by proposing and testing a communication-based protection system specifically tailored to fishermen. This system uses infrared, sound wave and other technologies to facilitate data exchange among various sensors;ultimately resulting in a robust tool with low costs for improving communication and security capabilities for fishermen. © 2023 IEEE.

关键词： Transmitters

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