2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)最新文献_第9页

Deep Learning with Heuristic Optimization Driven Diabetic Retinopathy Detection on Fundus Images 基于启发式优化的深度学习驱动眼底图像的糖尿病视网膜病变检测

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10140220

R. Ramesh, S. Sathiamoorthy

{"title":"Deep Learning with Heuristic Optimization Driven Diabetic Retinopathy Detection on Fundus Images","authors":"R. Ramesh, S. Sathiamoorthy","doi":"10.1109/ICAAIC56838.2023.10140220","DOIUrl":"https://doi.org/10.1109/ICAAIC56838.2023.10140220","url":null,"abstract":"Diabetic retinopathy (DR) is an illness occurred by the presence of diabetes which can resulted to blindness if left untreated. Identification of the DR at the benigning stage helps to prevent the loss of vision. Since deep learning (DL) models are commonly used for medical image analysis, it is used to classify the DR accurately. One of the effective way is to utilize a convolutional neural network (CNN) to classify retinal images as either normal or showing signs of DR. The CNN identifies the patterns and features in the images that are indicative of DR, such as the presence of microaneurysms, hemorrhages, exudates, or neovascularization. Therefore, this article presents an accurate DR grading and classification using Brain Storm Optimization with Deep Learning (DRGC-BSODL) algorithm. The DRGC-BSODL algorithm follows a three stage process. Initially, the contrast enhancement process is implemented. Next, the DRGC-BSODL model employs the BSO algorithm with multilevel thresholding (MLT) technique for image segmentation. Moreover, DenseNet169 model is exploited for generating a group of feature vectors. At the third stage, deep neural network (DNN) model is applied for DR classification. The simulation outcomes of the DRGC-BSODL model is tested on the fundus image dataset and the outcomes indicate the remarkable performance of the DRGC-BSODL model.","PeriodicalId":267906,"journal":{"name":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131600915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review and Trends on Hand Gesture Recognition of Sign Language based on Deep Learning Approaches 基于深度学习方法的手语手势识别研究进展与趋势

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10141353

Snehal Abhijeet Gaikwad, D. Upasani, Virendra Shete

{"title":"Review and Trends on Hand Gesture Recognition of Sign Language based on Deep Learning Approaches","authors":"Snehal Abhijeet Gaikwad, D. Upasani, Virendra Shete","doi":"10.1109/ICAAIC56838.2023.10141353","DOIUrl":"https://doi.org/10.1109/ICAAIC56838.2023.10141353","url":null,"abstract":"Hand gestures are observed as an effective tool for making the interaction in the community with individuals having intellectual disabilities. It is highly essential for communicating the computers and people. Therefore, it is aimed to design an automatic hand gesture recognition approach that is utilized for repeatedly performing human-computer interaction. Sign languages are considered the natural languages utilized by hearing-impaired people that involve some expressional way of communication in routine life. It reveals the sentences, words, and letters present in the spoken language for performing the gesticulations that enable communication between them. The deaf community makes communicates with normal people using an automation system that relates the signs with the words of speech. The hand gesture recognition system is implemented independently of requiring any unique hardware rather than using the webcam. Thus, it is highly significant to make a short review of hand gesture recognition based on deep learning techniques considering the Indian sign language. Hence, this paper discusses and clarifies existing research work based on hand gesture recognition in Indian sign language with algorithmic classification. This survey also compares different performance measures, datasets utilized, and also different tools used for the implementation. Then, upcoming research and also current research gaps in hand gesture recognition in Indian sign language are analyzed. This review on state-of-the-art hand gesture recognition for Indian sign language tools has shown their potential for providing the right solution in different real-life situations. It is hoped that the contents and illustrations in this paper assist researchers in laying a good foundation to inform their studies.","PeriodicalId":267906,"journal":{"name":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","volume":"29 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128731028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RFID Attendance System-Enabled Automated Hand Sanitizer Dispenser using IoT 使用物联网的RFID考勤系统自动洗手液分配器

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10140315

Kaveri K, Jervila R, Alhaseena Km, Naskath J

{"title":"RFID Attendance System-Enabled Automated Hand Sanitizer Dispenser using IoT","authors":"Kaveri K, Jervila R, Alhaseena Km, Naskath J","doi":"10.1109/ICAAIC56838.2023.10140315","DOIUrl":"https://doi.org/10.1109/ICAAIC56838.2023.10140315","url":null,"abstract":"A hand rub or hand antiseptic are other names for hand sanitizer. The main purpose of it is to get rid of common diseases from hands. Hand sanitizers can be liquid, foam, or gel-based. The majority of the time, it is used in their place when soap and water are not available for hand cleansing. Hand sanitizers are often used in supermarkets, hospitals, daycare facilities, schools, and other public spaces to prevent the spread of infection. Nearly everyone has seen significant effects from the COVID-19 epidemic, and manufacturers are not an exception. Personal hygiene has gained critical precedence over all other considerations in public space as people have become more cautious in their contacts with other people and items. Visitors may find hand sanitizers in many public areas; however they must be manually activated. Some no-touch hand sanitizer dispensers are commercially available to prevent any contact at all, but they are costly, and the majority of off-the-shelf commercial sanitizers cannot be automated. This article examines and evaluates contemporary approaches to achieving the sustainable development goal of good health and well-being by using automated hand sanitizer and attendance system. It comprises all modules, including the pupil counter, temperature measurement and hand sanitization using Internet of Things.","PeriodicalId":267906,"journal":{"name":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128772947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Densely Connected Dilated Convolutions with Time-Frequency Attention for Speech Enhancement 基于时频关注的密集连接扩张卷积语音增强

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10140871

Manaswini Burra, Pavan Kumar Reddy Yerva, Balaji Eemani, Abhinash Sunkara

{"title":"Densely Connected Dilated Convolutions with Time-Frequency Attention for Speech Enhancement","authors":"Manaswini Burra, Pavan Kumar Reddy Yerva, Balaji Eemani, Abhinash Sunkara","doi":"10.1109/ICAAIC56838.2023.10140871","DOIUrl":"https://doi.org/10.1109/ICAAIC56838.2023.10140871","url":null,"abstract":"This research study has proposed a Dilated Dense Time Frequency Attention Autoencoder (DDTFAAEC) model to perform real-time speech enhancement. The proposed model consists of a fully convolutional neural networks with time frequency attention (TFA). TFA blocks have been followed by the convolutional and dense layers in the decoder and encoder. By combining feature reuse, deeper networks, and maximal context aggregation, dense blocks and attention modules are used to assist in the process of feature extraction. TFA mechanism is designed to learn important information with respect to time, channel and frequency in Convolutional Neural Networks (CNN). At different resolutions, the context aggregation is achieved by using the dilated convolutions. To avoid the information flow from future frames, casual convolutions are used, therefore the network will be made applicable for the real-time applications. This research study utilizes the sub-pixel convolutional layers in the decoder for the purpose of upsampling. In terms of quality scores and objective intelligibility, the experimental result outperforms the already used methods.","PeriodicalId":267906,"journal":{"name":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","volume":"49 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115861182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Evaluation of Pulse Triggered Flip-Flops in 32 mm CMOS Regime 32 mm CMOS脉冲触发触发器的性能评价

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10141264

O. Shah, Kajul Sahu, Rakesh, Zaiba Ishrat, Kunwar Babar Ali, Satvik Vats

{"title":"Performance Evaluation of Pulse Triggered Flip-Flops in 32 mm CMOS Regime","authors":"O. Shah, Kajul Sahu, Rakesh, Zaiba Ishrat, Kunwar Babar Ali, Satvik Vats","doi":"10.1109/ICAAIC56838.2023.10141264","DOIUrl":"https://doi.org/10.1109/ICAAIC56838.2023.10141264","url":null,"abstract":"This article summarises the results of considerable research conducted on pulse-triggered flip-flops (P-FFs) with regard to power consumption and delay measurements. These performance metrics are determined for six of the most advanced P-FFs currently available. The flip-flops considered are the clocked pseudo-NMOS level-converting flip-flop (CPN-LCFF), the pulse-generator-free hybrid latch-based flip-flop (PHLFF), the dual dynamic node hybrid flip-flop (DDFF), the cross charge control flip-flop (XCFF), the conditional clock level-converting flip-flop (CC-LCFF), and the single-ended conditional capturing energy recovery (SCCER) flip-flop. The simulations are performed in SPICE using 32 nm CMOS technology. It was observed that SCCER has better power efficiency and DDFF has better speed efficiency at variations in voltage. For wide temperature changes, SCCER again outperformed other designs in power dissipation and DDFF outperformed other designs in terms of speed of operations. Among all the P-FFs, SCCER has the best power delay product (PDP), whereas CPN-LCFF has the worst.","PeriodicalId":267906,"journal":{"name":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117098943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Early Stage Chronic Kidney Disease Prediction using Convolution Neural Network 使用卷积神经网络预测早期慢性肾脏疾病

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10141322

N. Pareek, Deepika Soni, S. Degadwala

引用次数: 0

Plant Leaf Disease Detection using Machine Learning 利用机器学习进行植物叶片病害检测

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10140367

K. Prabavathy, Mokara Bharath, Kambam Sanjayratnam, Nicole Reddy, M. S. Reddy

{"title":"Plant Leaf Disease Detection using Machine Learning","authors":"K. Prabavathy, Mokara Bharath, Kambam Sanjayratnam, Nicole Reddy, M. S. Reddy","doi":"10.1109/ICAAIC56838.2023.10140367","DOIUrl":"https://doi.org/10.1109/ICAAIC56838.2023.10140367","url":null,"abstract":"Plant leaf disease detection is a critical task in modern agriculture to ensure better crop yield and quality. This provides a unique strategy for detecting plant leaf disease using machine learning techniques. The proposed methodology consists of three main stages, followed by classification using five different models, including KNN, SVM, Decision Trees, Random Forest, and CNN. The collected images are pre-processed to eliminate unwanted features, and the images are resized to a standardized size of $256times 256$ pixels. The following stage involves utilizing the pre-trained CNN model to extract pertinent features. The extracted features are then utilized to train the classification models. The performance of each model is assessed using various metrics, to predict its effectivity and accuracy. This proposed methodology is expected to provide a reliable and efficient diagnosis of plant diseases, helping farmers to take timely measures to prevent disease outbreaks and ensure healthy crop growth. The proposed system achieved high accuracy, less complexity, and easy identification. The experimental findings show that the suggested paradigm is successful in identifying common diseases. The suggested method of early detection and diagnosis of crop diseases can result in timely treatment and higher crop yield.","PeriodicalId":267906,"journal":{"name":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115415068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Emergency People Evacuation System using Crowd Density Detection and Path Finding Algorithm 基于人群密度检测和寻径算法的紧急人员疏散系统

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10140581

S. Samundeswari, S. Yogeshwaran, S. G. Krishnaa

引用次数: 0

Recevent: NLP based Event Recommender System Recevent:基于NLP的事件推荐系统

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10140251

Sanskar S Tare, Maitrey M Bhute, Pranav Arage

引用次数: 0

Malware Classification using Malware Visualization and Deep Learning 基于恶意软件可视化和深度学习的恶意软件分类

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Pub Date : 2023-05-04 DOI: 10.1109/ICAAIC56838.2023.10140600

Prabhpreet Singh, Priyanshu, Aruna Bhat

引用次数: 0