2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)最新文献

{"title":"Video Compression using Deep Neural Networks","authors":"Dayananda P, Siddharth Subramanian, Vijayalakshmi Suresh, Rishab Shivalli, Shrinkhla Sinha","doi":"10.1109/CCIP57447.2022.10058645","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058645","url":null,"abstract":"Advanced video compression is required due to the rise of online video content. A strong compression method can help convey video data effectively over a constrained bandwidth. We observed how more internet usage for video conferences, online gaming, and education led to decreased video quality from Netflix, YouTube, and other streaming services in Europe and other regions, particularly during the COVID-19 epidemic. They are represented in standard video compression algorithms as a succession of reference frames after residual frames, and these approaches are limited in their application. Deep learning's introduction and current advancements have the potential to overcome such problems. This study provides a deep learning-based video compression model that meets or exceeds current H.264 standards.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129412710","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}

{"title":"An Exploratory Analysis of GSDMM and BERTopic on Short Text Topic Modelling","authors":"Abhinandan Udupa, K. N. Adarsh, Anvitha Aravinda, Neelam H Godihal, N. Kayarvizhy","doi":"10.1109/CCIP57447.2022.10058687","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058687","url":null,"abstract":"Topic models may be a useful tool for locating latent subjects in collections of documents. Short text clustering has become a more important task as social networking sites like Twitter have gained popularity. Short text is characterised by high sparsity, high-dimensionality, and large-volume. These characteristics are challenging to overcome. Two of the most well-known short text modelling algorithms are BERTopic and the Gibbs Sampling Dirichlet Multinomial Mixture Model (GSDMM). GSDMM is a topic model which can infer the count of topic clusters automatically with a good compromise between the fullness and uniformity of the clustering results, and is fast to converge. BERTopic is a neural topic model that extracts coherent topic representations based on the semantic similarity of words and phrases in the and clustering with the help of a class-based form of TF-IDF. We compare these two algorithms in this paper to determine which model is more effective in short text topic modelling.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125385034","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}

{"title":"An Efficient Big Data Gathering in Wireless Sensor Network using Reconfigurable Node Distribution Algorithm","authors":"M. S, Basavaraju N M, S. N, Mahendra H N, P. S, Deepak B L","doi":"10.1109/CCIP57447.2022.10058620","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058620","url":null,"abstract":"In recent days, communication process is performed in wireless sensor networks (WSNs). The WSN is effectively reconstructed and accurately communicates the information to each corner of high-density nodes of cellular area. The main objective of this paper is to improve the data gathering of all sensor nodes and efficiently optimize the energy utilisation of each node in WSNs. The cluster head is identified in highly node distributed WSNs. The sink nodes during big data gathering are effectively utilized in WSNs with the help of Reconfigurable Node Distribution Algorithm (RNDA). The proposed algorithm procedure has been followed to address the big data gathering location in WSNs and mobilize the sink nodes in optimized location for proper communication in WSNs. The performance analysis and comparison between proposed and existing methods have been carried out with respect to energy efficiency, packet delivery ratio, packet ratio and transmission energy. The simulation result shows that the proposed method reduces energy consumption by 2 % in high density sensor node network communication process. The proposed method effectively selects the cluster head in WSNs to enhance the throughput packet delivery ratio and transmission energy.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125426856","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}

{"title":"Unauthorized Entry Control System and Automated Parking Slot Messaging System Using RFID","authors":"Nithish Paul, N. K. Sourav, M. Dakshayini","doi":"10.1109/CCIP57447.2022.10058682","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058682","url":null,"abstract":"Today as many institutions, corporate organizations, and office campuses lack with an automated Entry control system for unauthorizedvehicles also an efficient automated parkingsystem. This is being done manually with security people, who must go to each vehicle at the main gate and verify, whether the person in the vehicle belongs to that organization or not. Which is really a tediousjob, wastes time, causing congestion at the gate making the authorized person belonging to the organization toexperience the annoying delay at the main gate and also in parking their vehicle. The proposed RFID based IoT solution system in this paper tries to resolve this by allowing the security at the main gate for easily recognizing the authorized employee vehicle and making employee to get the message with appropriate parking slot number to his phone at the entrance itself. This completely avoids the traffic congestion at the gate and the problem of searching for parking slot in the campus or basement. This system also provisions the security staff to have the information on authorized and unauthorized vehicles with the vehicle number and entry time, and manage the parking space or slots effectively.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128350830","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}

{"title":"Implementation of Pipelined Architecture for Red Channel Compensation Unit for Underwater Image Processing in 45 nm technology","authors":"Rohit Pravin Mungekar, Navaneeth Krishna L S, R. Jayagowri, Vishwas P","doi":"10.1109/CCIP57447.2022.10058646","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058646","url":null,"abstract":"Underwater images obtained from sea is degraded in its quality due to absorption, scattering, bending of light etc. Red channel compensation is a major process in underwater image restoration which helps in avoiding the effect of red artifacts in the image. In this paper pipelined architecture is developed for red channel compensation unit. The architecture is synthesized for 45nm Technology node and simulated for its functionality verification at 100MHz of operating frequency. The IEEE-754 standard is used to store and access the image from memory. A method is proposed in the designed architecture intended for fast computation and power reduction.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130282374","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}

{"title":"Skin cancer detection using deep learning","authors":"J. Vineeth, S. Hemanth, C. V. Rao, N. Pavankumar, HS Javanna, C. Janardhan","doi":"10.1109/CCIP57447.2022.10058685","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058685","url":null,"abstract":"Skin cancer cases around the world have been increasing throughout the last decade. It is a major public health issue around the world. According to the World Health organization (WHo), 3 million cases of skin cancer are reported worldwide each year. The early detection of the disease is very important to increase patient prognostics. over the past ten years, there has been an increase in the usage of computer-aided diagnosis (CAD) devices for early detection of skin cancer. over the past years, skin cancer detection has been automated with AI concepts and image processing using the infected skin images. Deep learning models have recently shown promise in a variety of medical image processing tasks. An attempt has been made in our work to build a deep learning model using Convolution Neural Network (CNN) for early detection of the skin cancer using the skin images. The model is designed using various predominant features of skin cancer images for prediction. The model implements three different hidden layers with the hybrid combination of activation functions to achieve the accuracy of 95%. The model has the ability to make accurate predictions for unseen data values. The work implemented is expected to be helpful model in the early detection of skin cancer in the field of medicine and healthcare.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115773864","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}

{"title":"Design and Analysis of Power Optimization in Internet of Things using RFID based Energy Harvesting Mechanism","authors":"Manian Dhivya, G. Rajesh, A. B. Gurulakshmi, Puvirajan, Sanjeev Sharma","doi":"10.1109/CCIP57447.2022.10058640","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058640","url":null,"abstract":"One of the major concerns in using IoT devices is life of the battery, especially in remote places where power resources are limited. By employing certain low powered sensors, the IoT devices with higher power consumption can be activated only when required. In this paper, a methodology is proposed for reducing the consumption of power in an IoT device which sends data from a RFID tag to an output file. The consumption is reduced by implementing sleep mode when, the device is not required to be active, and a wakeup signal and studying the impact it has on the power consumption. An energy harvesting device is also integrated to make the device self-sustainable.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128467039","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}

{"title":"Real-time Water Quality Monitoring of Lakes using IoT based Remotely Operated Underwater Vehicle","authors":"Manian Dhivya, Bhawna Khokher","doi":"10.1109/CCIP57447.2022.10058681","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058681","url":null,"abstract":"Water degradation has become a critical theme of concern in recent years. Water is necessary for biological species survival and living activity is strikingly dependent on the quality of the water (i.e., physical, chemical, and biological aspects of water). The aim of the paper is to develop Internet-based Water Quality Monitoring System to determine the water quality parameters namely turbidity, PH, temperature etc. The developed model encompasses ESP32 Wi-Fi & Bluetooth Microcontroller with appropriate sensors and communication circuitry. The paper proposes a cost effective Remote Operated Underwater Vehicle which can monitor the parameters successively for prolonged period. The developed model is tested for three different cases and the parameters inferred are communicated through Thing Speak analytics platform","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132149750","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}

{"title":"Advanced Security Systems for Home Surveillance","authors":"G. Savitha, S. Aashish Ramana, K. Jain","doi":"10.1109/CCIP57447.2022.10058683","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058683","url":null,"abstract":"In modern times, Security and surveillance in households have become somewhat of an especially important necessity. Advancement in technology has made it possible for everyone to access or break into different houses easily. The main purpose of our project is to build an advanced surveillance system that can be used to detect the different faces or any movement that may occur while in the view of the surveillance camera. This system is also supported by an application that has unique features to make it more user friendly for the users. Not only is the user notified when an unauthorized entity is detected, the user is also allowed to add different faces or objects that will be ignored during the process of theft detection. This has been achieved using unsupervised machine learning where a given set of data is compared with the actual live feed from the surveillance camera to check for any anomalies in its surroundings. The Dataset or the data used in the proposed system are a few images in the format of. JPEG and. JPG which can be stored in the given location manually by the user or through the application itself. The proposed model recognizes the images in any of the available formats. The modules used in this system are powered by a strong python module named Open CV. This module supports various face recognition algorithms such as Haar Cascade, Eigen Faces, Fischer Faces, Local Binary Pattern Histogram (LBPH), etc and this module is responsible for all the image recognition, classification, and identification. The images extracted from the dataset are real time Image frames obtained from the user webcam, both are compared using the Face Recognition module in python which uses the Regions for - Convolutional Neural Network Algorithm (R-CNN) and Unsupervised learning approach to detect and differentiate between objects in Real Time. This system also includes a message transmitting feature which works with the help of the Simple Message Transfer Protocol (SMTP) module in python. Whenever an unknown user is identified by the system an email is sent to the admin or the user using the SMTP message transfer module which registers the mail address of the user when the initial setup of the system takes place. Hence a robust, secure and user-friendly device is developed that can always keep your house theft free.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122377861","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}

{"title":"Cover Page","authors":"","doi":"10.1109/ccip57447.2022.10058677","DOIUrl":"https://doi.org/10.1109/ccip57447.2022.10058677","url":null,"abstract":"Cover Page.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122853438","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}