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Augmented Intelligence and Sustainable Systems (ICAISS), International Conference on
2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)
23-25 Aug. 2023
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Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
Augmented Intelligence and Sustainable Systems (ICAISS), 2023 Second International Conference on
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Heritage Coin Identification using Convolutional Neural Networks: A Multi-Classification Approach for Numismatic Research
Publication Year: 2023,Page(s):1 - 6
Cited by: Papers (22)
Heritage coin identification and categorization is a complex undertaking that requires much knowledge. For the automated recognition and categorization of six heritage coins, including ancient Greek, Roman, Byzantine, Islamic, Indian, and Chinese coins, we suggest a deep learning-based method in this research study employing Convolutional Neural Networks (CNN). To boost the size and variety of the...Show More
A Futuristic Approach to Legal Studies with Artificial Intelligence
Nikhil Mishra;Rajesh Bahuguna;Shweta Pandey;Rajesh Singh;Aarushi Singh
Publication Year: 2023,Page(s):52 - 56
In the fast-moving world, the convergence of digitalization is unavoidable, thus, people are witnessing the technological advancement and automation in the various fields. This research study discusses about incorporating AI in Legal studies for the betterment of justice. The methodology used in this study focuses on the convergence of artificial intelligence with the legal system in order to take...Show More
An Enhanced Deep Learning Algorithms for Image Recognition and Plant Leaf Disease Detection
Publication Year: 2023,Page(s):611 - 615
Cited by: Papers (1)
Object recognition in photographs has only been possible with the advent of modern deep learning (DL) techniques. Following its success in other fields, DL techniques are increasingly being used to a broad variety of agricultural operations. Due to its intrinsic complexity, image-based plant disease detection is difficult to solve. Targeted management relies on more than just detection and require...Show More
Deep Convolutional Generative Adversarial Networks for Crime Scene Object Detection
Publication Year: 2023,Page(s):616 - 620
This research work introduces a novel technique to detect Crime objects by using perceptual adversarial networks and generative adversarial networks (GANs). Deep Convolutional GANs (DCGANs), Detecting Crime objects is difficult since standard object detection methods have restricted receptive fields and lose fine-grained data during the process. Our suggested framework takes advantage of the capab...Show More
Sleep Disorder Prediction on Polysomnography with EEG Signal using Machine Learning Algorithms
Publication Year: 2023,Page(s):621 - 626
This research study intends to predicts whether the patient is having sleep disorder or not. A dataset of EEG (electroencephalogram) signals, which are measurements of electrical activity in the brain are considered. The obtained signals are pre-processed to filter out any background noise, and then categorized by frequency analysis into four types of brain waves: alpha, beta, theta, and delta. Th...Show More
Pest Identification and Control in Paddy Plants using Ml with an Optimised Activation Function
Mohanraj. P;Rajasekar. T;Aksha Varshini. B;Charumathi. V. S;Dhaarani. S
Publication Year: 2023,Page(s):627 - 631
The rice plant, one of the most extensively cultivated crops in India, suffers from a number of diseases at various stages of its growth. Farmers find it incredibly difficult to manually diagnose these diseases properly because of their lack awareness. Caused by many types, Such as; Fungi, Bacteria and Viruses and Pest. In Image processing technology many algorithms are used to classify rice leaf ...Show More
A Brief Survey on Multi Dimensional Feature Subset Based Lung Tumor Identification Model using Machine Learning Techniques
Publication Year: 2023,Page(s):632 - 637
Identifying malignant lung nodules from Computed Tomography (CT) scans is a complex and time-consuming task for radiologists. To ease this burden, Computer-Aided Diagnostic (CAD) systems have been developed. Over the past few years, approaches to deep learning have demonstrated excellent outcomes, often beating classical methods. Researchers are currently experimenting with a variety of deep learn...Show More
Augmented Intelligence in Machine Learning for Cybersecurity: Enhancing Threat Detection and Human-Machine Collaboration
Santosh Gore;Sajeesh Hamsa;Sujata Roychowdhury;Gayatri Patil;Sujata Gore;Sayali Karmode
Publication Year: 2023,Page(s):638 - 644
Cited by: Papers (2)
Analysts can combat sophisticated cyber-attacks thanks to enhanced intelligence in cyber security, which blends human experience with developments in machine learning and image processing. This cooperative strategy acknowledges the importance of both human discretion and technological intelligence in the safeguarding of digital assets. To improve threat detection and foster human-machine collabora...Show More
An Innovative Method to Increase Agricultural Productivity using Machine Learning-based Crop Recommendation Systems
Publication Year: 2023,Page(s):645 - 651
Cited by: Papers (1)
A research study was conducted to address the issue of Indian farmers relying on traditional practices and being highly influenced by weather conditions. This research aimed to assist farmers by recommending suitable crops based on their specific circumstances and environmental factors such as soil composition, pH value, rainfall, and humidity. The researchers utilized seven machine learning model...Show More
A Deep Learning Framework for Prediction of Heart Diseases from Clinical Observations
Publication Year: 2023,Page(s):652 - 656
Cited by: Papers (1)
Among today's youth, heart disease has emerged as a major health concern. Many forms of cardiac disease can be traced back to bad habits and clinical characteristics. Many other models have been proposed by researchers to aid in the diagnosis of various conditions, however the vast majority either has poor accuracy performance or are overly complex to implement in real-time clinical settings. In a...Show More
Emotion Recognition using Machine Learning Models on Electroencephalogram (EEG) Data
Publication Year: 2023,Page(s):657 - 662
Analyzing Electroencephalogram (EEG) data using cutting-edge machine learning techniques to comprehend emotional states. EEGs are non-invasive and have been shown to illuminate the complex neural mechanisms at play during affective experiences in the human brain. Everything is addressed in detail, from data collection and organization to feature extraction for model training and evaluation. It has...Show More
Feature Engineering and Machine Learning for IoT-based Applications: An Overview of Algorithms
Publication Year: 2023,Page(s):663 - 668
This paper presents an overview of machine learning algorithms for feature valuation in IoT-based applications. The increasing use of IoT devices has led to a vast amount of data generated from sensors, which require analysis and interpretation. Machine learning algorithms can help extract useful information from this data and enable IoT devices to make intelligent decisions. The paper begins with...Show More
Enhanced Banking Services using Blockchain and Artificial Intelligence
Sumit Nirvan;Sandhya Verma;Samta Kathuria;Rajesh Singh;Shaik Vaseem Akram
Publication Year: 2023,Page(s):57 - 62
Cited by: Papers (2)
The advancement of technology has given a new dimension to various sectors and this paper particularly talks about banking sector. The purpose of writing this paper is to understand how the technology such Artificial intelligence (AI) and Blockchain works in the various elements of the financial sector to make it more effective with optimum utilization of resources, accuracy of predictions and dec...Show More
Crop Selection and Yield Prediction using Machine Learning Algorithms
Publication Year: 2023,Page(s):669 - 673
Cited by: Papers (3)
Agriculture monitoring, particularly in developing nations, can assist prevent famine and aid human efforts. Estimating crop yields before harvest, often known as yield estimation, is difficult. Our technique predicts agricultural yields using publicly available remote sensing data in a scalable manner. Accurate, and economical manner. This strategy might assist all farmers use the least amount of...Show More
X-Ray Image Analysis using Deep Learning Techniques to Identify Pneumonia
Ashok Reddy Kandula;Sri Divya Gangiredla;Krishna Priya Tirukkovalluri;Sreshta Yallamilli;Nikhitha Tummalapalli;Sathwika Talluri
Publication Year: 2023,Page(s):674 - 679
Cited by: Papers (7)
Most frequently, viruses or bacteria cause respiratory infections that are severe like pneumonia. It is the most common infectious killer of children worldwide and can cause mild to severe illness in people of all ages. It is generated by bacteria, viruses, or fungi and is transmitted through contact via air. The main goal is to build Convolution Neural Network models for classification of pneumon...Show More
Smart Blind Assistant using Deep Learning for the Visually Impaired Users
Vijaya Vardan Reddy S;B. Sathyasri;J. Joselin Jeya Sheela;Malarvizhi. C;S. Vanaja;Shyam. S
Publication Year: 2023,Page(s):680 - 684
In today’s modern world, visually impaired and blind people experience numerous difficulties in driving their daily need and life. They had undergone many challenges in strange environment without a manual aid who insist in helping them. As the technology is gradually increasing day by day, there exists various opportunities in helping out the blind and visually impaired people. The proposed work ...Show More
Road accidents are a major cause of injury and death worldwide, and there is a need for accurate and proactive accident prevention measures. In recent years, Internet of Things (IoT) devices have been increasingly used for collecting real-time data on various parameters that affect the likelihood of accidents, such as weather conditions, traffic volume, and road conditions. Additionally, deep lear...Show More
Machine Learning Method for Recognizing Human Eye Pupil Region
R. Rajkumar;Gokulavani D;Rajesh K;Nagaiah Apuri;T. Chandrasekar;R Benazir Begam
Publication Year: 2023,Page(s):693 - 698
This research study describes how machine learning techniques can be employed to segment human pupils. The objective is to recognize and isolate the pupil region in ocular images. The aspects of a methodology are data set preparation, feature extraction, machine learning model selection, model training, model optimization, model testing, model evaluation, and finally post-processing. During prepro...Show More
A Comprehensive Analysis of the Developments and Applications of Deep Learning in Citrus Plant Disease Detection
Publication Year: 2023,Page(s):699 - 703
Cited by: Papers (1)
Due to their great demand for both consumption and non-consumption applications, citrus plants are the most sought-after crop internationally. Therefore, producers take care to eradicate illnesses that affect citrus plants during their growing stage in order to maximize harvest. Even while they usually do this by using their own experience, this strategy is inappropriate when the orchard is huge a...Show More
The term "Cloud Computing" (CC) refers to the on-demand availabilities of network resources, in particular data storage and processing powers. It is a collection of contemporary public and private data centers that generate clients with a unified platform through the Internet. A developing paradigm in computing, cloud computing puts processing and data storage closer to the consumers to speed up r...Show More
Galvanic Skin Response based Stress Detection System using Machine Learning and IoT
Ayalapogu Ratna Raju;R. Ramadevi;Padamata Ramesh Babu;Vetriselvi D
Publication Year: 2023,Page(s):709 - 714
Cited by: Papers (2)
The primary objective of this study is to construct an Internet of Things (IoT)-based stress detection system that uses Galvanic Skin Response (GSR) and pulse sensors. In today's contemporary world, stress has developed into a widespread problem and early recognition of the condition is necessary for efficient intervention and treatment. The suggested system utilizes GSR and pulse sensors in conju...Show More
Automated Personalized Health Analytics using IoT and Machine Learning Algorithms
Publication Year: 2023,Page(s):715 - 719
This research work develops and implements an integrated system using IoT technologies and machine learning algorithm to measure Body Mass Index (BMI) and perform health analytics in hospitals. Obesity, overweight, and chronic diseases are major public health issues. Healthcare workers need accurate and quick BMI readings to monitor weight status and health issues. To overcome these limitations, t...Show More
A Comparative Analysis of Machine Learning Approaches for Fake News Detection
Publication Year: 2023,Page(s):720 - 725
Considering it has an opportunity to harm society and the nation, the proliferation of fake news via social media platforms is a major cause for worry. There have been several searches for it. This research study assesses the investigation and legalization of fake news identification and reveals some of the most popular machine learning regulations to end up generating an accurate representation o...Show More
TCP-CNNLSTM: Congestion Control Scheme for MANET using AI Technologies
Publication Year: 2023,Page(s):63 - 69
The primary focus of the research is on how artificial intelligence techniques may be applied to MANETs to improve communication and safe routing between mobile dynamic nodes. In this paper, a proposed machine learning-based congestion control method, the TCP-CNNLSTM model. This model works in the classification and decision-making process. It collects network traffic traces, selects a few factors...Show More
A New Wide-Angle, Low-Resolution Infrared Array Sensor with Improved DL Algorithm for Activity Detection
S. Poorani;M. Karthick Raja;B. Parkavi;Soumitra Subodh Pande;Arunmurugan Subbaiyan;S. Kiruthiga
Publication Year: 2023,Page(s):726 - 731
A deep learning based method for activity detection that makes use of low-resolution, wide-angle infrared (IR) array sensors. In addition to the primary difficulty of this work—how to further enhance the performance of IR array sensor-based systems for activity detection also tackle the following issues: When comparing to a regular IR array sensor, a wide-angle sensor is used to get a better overa...Show More
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
Augmented Intelligence and Sustainable Systems (ICAISS), 2023 Second International Conference on
- DVDPurchase at Partner
- Print on DemandPurchase at Partner
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