collaboration 1collaboration 1collaboration 1collaboration 1collaboration 1
cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1cci-project1
Centre for Machine Learning and Intelligence is a ISO Certified(ISO/IEC 20000 - 1: 2018) centre formed for students, consisting of both undergraduate and postgraduate who are interested in Artificial Intelligence and seek a place to talk about it. The goal is to form a community of interested students who share knowledge, passion, and skills. The centre focuses around Artificial Intelligence, Machine Learning and Deep Learning and its application in the domain of Health care, Agriculture, Smart cities, Education, Transport etc.
Facilities
AI Core Research Lab
The aim of this AI Core Research lab is to raise awareness about AI and its practical applications. And to support multidisciplinary research that addresses the real-world challenges and advancement of AI technologies. AI-based projects were given to various departments and students to strengthen AI in the multidisciplinary field. Around 94 projects were done using AI techniques, of those 22 are multidisciplinary projects. AI related courses were introduced for Bioscience, Home Science and Business Administration students to enhance their knowledge of AI and how to use it in different field to solve problems. The uniqueness of the centre is to facilitate the students and researchers by bridging them to the mentors of the required domain. The centre also expands its boundary by collaborating with foreign universities like University of Wyoming, USA, Hassan II University, Morocco, Athabasca University, Canada and Kyungpook University, South Korea.
AAI Startup programme
About the programme
AAI Lab is a research platform for exploring the potential of students with Internet of Things for multidisciplinary research with more end-user interactions. It gives the power to the students to be at the core of the research and innovation process. It gives them the power to change the world and their future. AAI lab is equipped with micro controllers, RFID tags, different types of sensors. In the lab we have a 3D printer to develop multi disciplinary products. We have AVR software to engaged in the design and development of advanced human-machine interfaces for students. We will cultivate the spirt of technology based agriculture among the students with the help of farm bot deployed in our center. By using this lab, students could develop IoT proof of concepts, learn embedded programming and create their own prototypes.
IoT Lab transforms ideas of the student into customized solutions for the problems of the society. Also we will encourage students to participate in many competitions.
Thrust areas
1.Farm Bot
Farm automation, often associated with smart farming. It is a robot to farm the different crops in particular area. The robot itself moves around using tracks on the sides of the box, and it works in three dimensions. So it can go left to right, forward and backwards, up and down. FarmBot sows seeds, waters plants and gets rid of weeds by using different tools for each job, depending on the task at hand. It monitors the plant 24*7. In our centre we will deploy the farmbot in order to cultivate the spirit of agriculture among the students. We will use drones to fertilize the plants. With the help of captured pictures from the drone, can implement Image Processing applications for further research work.
2.Augmented Reality
Augmented reality (AR) is an enhanced version of the real physical world that is achieved through the use of digital visual elements, sound, or other sensory stimuli delivered via technology. Primary goals of AR is to highlight specific features of the physical world, increase understanding of those features, and derive smart and accessible insight that can be applied to real-world application.
3.University Automation
A university automation system will monitor and control attributes such as light, climate, entertainment systems and appliances. It may also include centre's security system such as access control and alarm systems with the help of IoT.
4.Renewable energy - Solar energy
A renewable energy source means energy that is sustainable. Similar to sun, Solar Power is main source of renewable source. Solar power is energy from the sun that is converted into thermal or electrical energy. Solar technologies can harness this energy for a variety of uses, including generating electricity for our center. We will deploy a Solar cell which can drive upto 1000 Kilowatts in our university. The energy driven from the solar cells can be used instead of electricity. This will predominantly save electricity consumption.
AI Cloud Centre
AI Cloud Centre revolutionizes the Institution by facilitating with AI as a service. It also facilitates the students with higher end experience in the process of learning AI Cloud by steering and involving them in various best practices and established state of the art in the development and innovation of machine learning and computational algorithms. This facility acted as a hub for learners and innovators to involve in cloud-based AI projects and also supported and organized the activities in collaborations between AI cloud research groups from different fields in the University, promoting the interdisciplinarity which is the key research vision of the Institute. The Centre provided Infrastructure as a Service, Storage as a Service, Software as a Service, Data as a Service, Artificial Intelligence and Machine Learning Frameworks and Cognitive Computing Interfaces (APIs).
Facilities
i. Hardware
1.Server -I (SuperMicro)
2.Server-II(DellEMC)
3.Server-II (Supermicro GPU Server)
ii. Software
1.Schrodinger
2.Sigma Plot
3.PRISMA
4.Python
5.GSuite for Education
6.CUDA
7.Annaconda3
8.Cmake3
9. Android Studio
10. R studio server
11.Gromacs
12.Orange (Data mining)
13.MATLAB
14.Desmond
15.VScode
16.Weka
17.Amira
18.Mathematica
AI Library
AI Library is established under DST-CURIE-AI-Phase – II. This library contains AI-related books, computer science books, and books on AI in multidisciplinary fields.
CMLI - Learning Management system
Vision AI
Adaptive Learning 1.0
Technology Enabled Learning
Farm Intelligence
Augmented Reality & Virtual Reality
Internet of Things
Services
GPU Based Computational Drug Discovery
Software tools provided for Computational Drug Discovery and Molecular Docking Analysis
1.Schrodinger 2.Gromacs
Computational Drug Discovery and Molecular Docking Analysis
1. Molecular Docking of selected Drug target and Ligand 
§ Identification of potential Drug Target
§ Active sight prediction / Inhibitor Binding sight prediction
§ Selection of Ligands / Inhibitors
§ 2D and 3D Interaction Plots, Binding Energy
2. Post Docking Analysis
§ MMG-GBSA
§ Molecular Dynamic Simulation using Desmond / GROMACS
3. Protein Protein Docking
4. Interpretation of results
5. Dataset curation / validation etc
Those who wanted to make use of this facility, Click here
GPU Based Computational Drug Discovery Charges
Consultancy & Service Charges – GPU based Schrodinger Suite Modules(Click here to view in a PDF)
| S.No. | Description | For Normal Data in Rs.(up to 200 NS) |
| 1. | Molecular Docking - Ligand preparation, Protein preparation |
|
| Server Processing,GPU Utilization & Memory usage
|
Memory Usage |
|
|
For up to 1 MB Rs.500 More than 1MB 5 per MB For up to 1GB 1000 More than 1GB 1000 per GB |
||
|
GPU Utilization time For up to 24 hours Rs.100 More than 24 hours Rs.5 per hour |
||
| 2. ADME Profiling |
200 (up to 50 Compounds) |
|
| 3. Molecular and High Throughput Virtual Screening | ||
| Server Processing,GPU Utilization & Memory usage |
Memory Usage For up to 1 MB Rs.500 More than 1MB 5 per MB For up to 1GB 1000 More than 1GB 1000 per GB GPU Utilization time For up to 24 hours Rs.100 More than 24 hours Rs.5 per hour |
|
| 4. Active Site Prediction | Rs. 200 per protein | |
| 5. Protein Structure Prediction | ||
| Server Processing,GPU Utilization & Memory usage |
Memory Usage For up to 1 MB Rs.500 More than 1MB 5 per MB For up to 1GB 1000 More than 1GB 1000 per GB GPU Utilization time For up to 24 hours Rs.100 More than 24 hours Rs.5 per hour |
|
| 6. QSAR | ||
| If strutural analogs to be prepared | Rs.5000 | |
| If they bring structural analog (100 Nos) | Rs.1000 | |
| 7. Molecular Modelling and Simulation | ||
| 1. Minimum Charges (up to 24 hrs Computer time) | Rs.2500 | |
| 2. Every additional hour of computer time | Rs 50 per hour | |
| 8. Service Charges | Rs. 25 per hour | |
Those who wanted to make use of this facility, Click here
AI and IoT Based Modules, Interfaces , Mobile Applications, Portal etc
Centre for Machine Learning and Intelligence is providing 'AI as a Service' to all the Researchers of our Institution. The kind of service to be provided will be
1.Artificial Intelligence and Machine Learning Frameworks
§ Google Cloud Platform
§ Google AutoML
§ Google Vision API
2.Cognitive Computing Interfaces (APIs)
§ Google Cloud Platform APIs
§ Natural Language Processing
§ Development and offering of AI & ML interfaces
Those who wanted to make use of this facility, please fill in this Google form click here
Centre for Machine Learning and Intelligence is providing 'AI Cloud Services' to all the Researchers of our Institution. The kind of service to be provided will be
Storage as a Service
3. Software tools provided for molecular modeling, drug discovery, and docking
Those who wanted to make use of this facility, please fill in this Google form click here
AI and IoT Based Modules, Interfaces , Mobile Applications, Portal etc charges
Consultancy & Service Charges - AI and IoT based Modules, Interfaces, Mobile applications, portals etc.
| S.No | Description | Amount in Rs. | |
| Inside Institution | Outside Institution | ||
| 1. | AI / IoT based Modules | Rs.500 / Module | Rs.1000 / Module |
| 2. | AI / IoT based Interfaces | Rs.500 / Interface | Rs.1000 / Interface |
| 3. | Mobile Application | Rs.500 /Module | Rs.1000 / Module |
| 4. | AI and IoT based digital portal | Rs.500 / Module | Rs.1000 / Module |
Peoples
Coordinators
Dr.P.Subashini
Coordinator
Centre for Machine Learning and Intelligence
Mail id : subashini_cs@avinuty.ac.in
https://avinuty.ac.in/user/csc15018
https://in.linkedin.com/in/p-subashini-14a72119
https://www.researchgate.net/profile/Parthasarathy-Subashini
Dr.M.Krishnaveni
Co-coordinator
AAI Startup PROGRAMME
Mail id : Krishnaveni_cs@avinuty.ac.in
https://avinuty.ac.in/user/csc22013
https://in.linkedin.com/in/krishnaveni-marimuthu-51274219b
https://www.researchgate.net/scientific-contributions/M-Krishnaveni-15234651
Dr.R.Janani
Research Assistant
Centre for Machine Learning and Intelligence
Mail id : Janani_cmli@avinuty.ac.in
https://www.researchgate.net/profile/Janani-Balakumar
Ms.R.Shanmugavalli
Research Scholar
Department of Computer Science
Centre for Machine Learning and Intelligence
Research Work Title: Energy Aware Route Discovery Mechanism using Various Optimization Algorithms in Wireless Sensor Network
Mail id : 17phcsf004@avinuty.ac.in
Mrs.Jennyfer susan M B
Research Scholar
Department of Computer Science
Centre for Machine Learning and Intelligence
Research Work Title: Specular Reflection Removal in Smart Colposcopy Images Using Deep Learning Models for Enhanced Grading of Cervical Cancer
Mail id : 19phcsf008@avinuty.ac.in
https://scholar.google.com/citations?user=4y1bWZUAAAAJ&hl=en
Mohana M
Research scholar, Senior Research Fellow (SRF)
Department of Computer Science
Centre for Machine Learning and Intelligence
Research Work Title: Facial Expression Recognition of Learners and Improving learners QoE
Mail id : mohana_cs@avinuty.ac.in
https://www.linkedin.com/in/mohana-m-84a435231
https://www.researchgate.net/profile/Mohana-Murugan
Aiswarya S
Research scholar
Department of Computer Science
Centre for Machine Learning and Intelligence
Research Work Title: Detection of Sickle cell disease using image processing and Deep learning Techniques
Mail id : 21phchf007@avinuty.ac.in
https://www.linkedin.com/in/aiswarya-senthilvel-b81720305/
https://www.researchgate.net/profile/Aiswarya-s-7
Mrs.Bhuvaneswari S
Research scholar
Department of Computer Science
Centre for Machine Learning and Intelligence
Research Work Title: Deep Learning for Grading Non-Proliferative Diabetic Retinopathy (NPDR) Based on Multi-level Lesion Detection.
Mail id : bhuvaneswari_cs@avinuty.ac.in
www.linkedin.com/in/bhuvaneswari-s2405
https://www.researchgate.net/profile/Bhuvaneswari-S-3
Ms.Jayashree Ganeshkumar
Research scholar
Department of Computer Science
Centre for Machine Learning and Intelligence
Research Work Title: Adaptive Learning
Mail id :jayashreegk30@gmail.com
https://www.researchgate.net/profile/Jayashree-Ganeshkumar
Ms.V.Narmadha
Technical Assistant
AAI Startup Programme
Mail id : narmadha_cs@avinuty.ac.in
Ms Sandiya C
Technical Assistant
Centre for Machine Learning and Intelligence
Mail id : Sandiya_cmli@avinuty.ac.in
Ms.Vasundra .R.S
Faculty cum-coordinator
Scopik Edutech Pvt Ltd
I. UG Programme
II. PG Programme
III. Certificate Course
IV.Generic Elective Courses
V. Skill Based Elective Courses
VI. Multidisciplinary Courses
Patent Granted - 2
1.Kidbot 1.0 -An adaptive learning-based robot using Tamil language is proposed that interactively disseminate machine learning concepts to Kids,Patent Number : 503234 , 25 Jan 2024.2.Cervical Cancer Self-Test Kit –IoT based device that allows users to independently operate and conduct self-screening tests Application No.-202241021066,May 2022.
Patent Published - 2
1.Mosquito Detection Device -AI-IoT based mosquito trap is proposed that detect mosquitoes species which are transmitting vector- borne diseases, Application No.-202241020392,May 2022.
2.AI based Binocular Wearable Potential Acuity Teaster May 2024.
1.Explore Python for Mathematics Authors Prof.P.Subashini, Dr.N.Balamani, Dr.R.Janani - "Click here"
2.Machine Learning using Google Colab Authors Prof.P.Subashini, Dr.T.T.Dhivya Prabha, Ms.M.B.Jennyfer Susan - "Click here"
3.Prototype Experiments for Beginners - Embedded Systems Authors Dr.M.Krishnaveni, Dr.P.Subashini, Ms.V.Narmadha "Click here"
4.Nature Inspired Computing Authors Dr.P.Subashini, Dr.T.T.Dhivya Prabha, Dr.M.Krishnaveni - "Click here"
5.I am your Android - Volume I Authors Dr.M.Krishnaveni, Dr.P.Subashini, Ms.B.Preethi- "Click here"
6.I am your Android - Volume II Authors Dr.M.Krishnaveni, Dr.P.Subashini, Ms.B.Preethi- "Click here"
1. Krishnaveni, M., Subashini, P., Dhivyaprabha, T.T., Gayathre, B., Manimegalai, K. (2023). Artificial Intelligence–Internet of Things Enabled Mosquito-Based Diseases Identification Trap. In: Hassanien, A.E., Zheng, D., Zhao, Z., Fan, Z. (eds) Business Intelligence and Information Technology. 2022. Smart Innovation, Systems and Technologies, vol 358. Springer, Singapore. DOI: https://doi.org/10.1007/978-981-99-3416-4_64.
2. M.B. Jennyfer Susan, P. Subashini, and M. Krishnaveni. (2023). Artificial Intelligence of Things for Smart Healthcare Development: An Experimental Review. In P. Swarnalatha & S. Prabu (Eds.), Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT, pp. 29-60. IGI Global. DOI: https://doi.org/10.4018/978-1-6684-8098-4.ch003
3. Subashini, P., Dhivyaprabha, T.T., Krishnaveni, M., Jennyfer Susan, M.B. (2023). Smart Intelligent System for Cervix Cancer Image Classification Using Google Cloud Platform. In: Ahad, M.A., Casalino, G., Bhushan, B. (eds) Enabling Technologies for Effective Planning and Management in Sustainable Smart Cities. Springer, Cham, PP. 245-281. https://doi.org/10.1007/978-3-031-22922-0_10.
4. M., Mohana., K., Nandhini., & P., Subashini. (2022). Review on Artificial Intelligence and Robots in STEAM Education for Early Childhood Development: The State-of-the-Art Tools and Applications. In A. Betts, & K. Thai (Ed.), Handbook of Research on Innovative Approaches to Early Childhood Development and School Readiness (pp. 468-498). IGI Global. https://doi.org/10.4018/978-1-7998-8649-5.ch019 (Book Name : Handbook of Research on Innovative Approaches to Early Childhood Development and School Readiness )
1. Jennyfer Susan M B, Subashini P, Krishnaveni M, Indhumathi T, "Detection of Specular Reflection from Smart Colposcopy Image using RGB Color Space and Convolutional Neural Network," International Journal of Engineering Trends and Technology, vol. 71, no. 10, pp. 29-38, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I10P204 (Scopus)
2. R. Shanmugavalli and P. Subashini, “Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utilization in Wireless Sensor Network”, International Journal of Computer Networks & Communications (IJCNC), vol. 15, no. 4, pp. 73-92, July 2023. ISSN: 0975-2293, E-ISSN: 0974-2293, (Scopus Indexing). DOI: 10.5121/ijcnc.2023.15405. Publisher Name: AIRCC Publishing Corporation URL: https://aircconline.com/abstract/ijcnc/v15n4/15423cnc05.html
3. Mohana, M., Subashini, P., & Krishnaveni, M. (2023). Emotion Recognition from Facial Expression using Hybrid CNN-LSTM Network. International Journal of Pattern Recognition and Artificial Intelligence. VOL. 37, NO. 08 https://doi.org/10.1142/S0218001423560086 (Impact factor: 1.5, Scopus and Web of Science indexed)
4. M.B. Jennyfer Susan, P. Subashini. (2023). Deep Learning Inpainting Model on Digital and Medical Images – A Review, International Arab Journal of Information Technology. Vol. 20, No. 6. (Article in Press - WoS and Scopus)
5. M.B. Jennyfer Susan, P. Subashini. (2023). Improvising Grading of Cervical Cancer using Quality Assessments method in Smart Colposcopy Images, Measurement Sensors, Vol. 27, No. 3, pp. 1-11. DOI: 10.1016/j.measen.2023.100788. (Scopus).
6. R. Keerthana, N. Valliammal, T.T. Dhivyaprabha and P. Subashini. (2023). A healthy nutrition suggestion model for indian women sports players & active youth using long short-term memory. Internet Technology Letters, Special Issue Article, pp. 1-6. DOI: https://doi.org/10.1002/itl2.452, Indexing in Scopus and WoS (E-SCI), Impact Factor: 1.7.
7. M.B. Jennyfer Susan, P. Subashini, and M. Krishnaveni. (2022). "Comparison of various deep learning inpainting methods in smart colposcopy images", International Journal of Computational Intelligence Studies, 11(1), 53–72. https://doi.org/10.1504/ijcistudies.2022.123347 (UGC-CARE).
8. G.Indumathi, K.Vetriselvi, Dr.K.Manimegalai, Dr.D.Mathivathani, “ Detection of Anopheline Mosquitoes from microscopic images using Image Processing", Journal of Huazhong University of Science and Technology , Volume 50, Issue 06, June-2021. ISSN-1671-4512
9. Dr. P. Sasirekha and Mageswari.S.S (2021) “Digital Banking: the New Normal”, SPAST Abstracts, 1(01). Available at: https://spast.org/techrep/article/view/1843.
1. Mohana, M., da Silveira, A.C., Subashini, P., Santos, C.A.S., Ghinea, G. (2023). Technology Enhanced Mulsemedia Learning: Insights of an Evaluation. In: da Silva, H.P., Cipresso, P. (eds) Computer-Human Interaction Research and Applications. CHIRA 2023. Communications in Computer and Information Science, vol 1997. Springer, Cham. https://doi.org/10.1007/978-3-031-49368-3_3
2. M. Mohana, N. Valliammal, V. Suvetha, M. Krishnaveni, P. Subashini and G. Ghinea, "A Study on Technology-Enhanced Mulsemedia Learning for Enhancing Learner's Experience in E-Learning," 2023 International Conference on Network, Multimedia and Information Technology (NMITCON), Bengaluru, India, 2023, pp. 01-06, doi: 10.1109/NMITCON58196.2023.10275964.
3. M. Mohana, Aleph Campos Da Silveira, V. Suvetha, P. Subashini, Gheorghita Ghinea, and Celso Alberto Saibel Santos. 2023. Technology Enhanced Mulsemedia Learning (TEML) for Learners with Dyslexia. In ACM International Conference on Interactive Media Experiences Workshops (IMXw ’23), June 12–15, 2023, Nantes, France. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3604321.3604357
4. M. Mohana and P. Subashini, "Emotion Recognition using Autoencoders: A Systematic Review," 2023 International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS), Coimbatore, India, 2023, pp. 438-443, doi:10.1109/ICISCoIS56541.2023.10100563. Source Link: https://ieeexplore.ieee.org/document/10100563
5. Krishnaveni, M., Raajeswari, P., Subashini, P., Narmadha, V., Ramya, P. (2023). Soil Nutrient Prediction Model in Hybrid Farming Using Rule-Based Regressor. In: , et al. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-031-27762-7_16
6. P. Subashini, M. Krishnaveni, T.T. Dhivyaprabha, R. Malini, V. Keerthika, G. Kaviya. (2023). A Contemporary Study on Solar Energy Applications and Evaluation in Real-Time Environment. NCMRSI 2023: Proceedings of the National Conference on Multidisciplinary Research for Sustainable Innovations, Coimbatore, pp. 138-150, ISBN: 978-81-931101- 6 - 4.
7. P. Subashini, M. Krishnaveni, T.T. Dhivyaprabha, M. Mohana, S. Divyasri. (2023). Artificial intelligence-based Totbot Application for Primary School Children. NCMRSI 2023: Proceedings of the National Conference on Multidisciplinary Research for Sustainable Innovations, Coimbatore, pp. 126-137, ISBN: 978-81-931101- 6 - 4.
8. Mohana, M., Subashini, P. (2023). Convolutional Sparse Autoencoder for Emotion Recognition. In: , et al. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-031-27762-7_1
9. Bhuvaneswari, S., Subashini, P. (2023). Red-Channel Based Iris Segmentation for Pupil Detection. In: , et al. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-031-27762-7_22
10. M. Mohana and P. Subashini, "Emotion Recognition using Deep Stacked Autoencoder with Softmax Classifier," 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), Coimbatore, India, 2023, pp. 864-872, doi: 10.1109/ICAIS56108.2023.10073937.
11. M.B. Jennyfer Susan and P. Subashini. (2022). "Detection of specular reflection on the smart colposcopy images using fine-tuned U-Net convolutional Neural Network". First International Conference on Technologies, Sustainable Development Goals and Academia (ICTSGA-1). Taylor and Francis Publisher. (Accepted)
12. International Conference on “Artificial Intelligence – Multidisciplinary Perspectives on Emerging Challenges, Research and Opportunities”: ICAI - 2022 Abstract Proceedings, in P. Subashini, N. Valliammal, M. Krishnaveni, G. Sudhamathy and M. Thilagu (eds.), Notion Press, April 2022, pp. 1-60, ISBN: 979-8886677430
13. G. Padmavathi, D. Shanmugapriya and A. Roshni, "Performance Analysis of Unsupervised Machine Learning Methods for Mobile Malware Detection," 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), 2022, pp. 201- 206, doi: 10.23919/INDIACom54597.2022.9763180
14. G. Padmavathi, D. Shanmugapriya and S. Asha, "A Framework to Detect the Malicious Insider Threat in Cloud Environment using Supervised Learning Methods," 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), 2022, pp. 354- 358, doi: 10.23919/INDIACom54597.2022.9763205
15. M.Mohana, Dr.P.Subashini (2021), “Comparison of Viola-Jones and Multi-Task Convolution Neural Network (MTCNN) for Face Detection from Children Facial Expression using Video Sequences” in the International Conference on Artificial Intelligence – Multidisciplinary Perspectives on Emerging Challenges, Research, and Opportunities (ICAI-2022) Organized by the Centre for Machine Learning and Intelligence, DST-CURIE-AI, during Feb 24th & 25th, Coimbatore, TamilNadu. ISBN-13 : 979-8886677430 (Abstract Only).
16. Narmadha.V, Valliammal.N,” Detection and Prevention of Cyber Harassment against Women in Social Media using Supervised Learning Algorithm”, Proceedings of ICTARA2020, ISBN-978-81-937760-4-9,2020
17. Ms. Roshni A, Dr. Kalpana B, "IoT Based Smart Home Automation and Personalization System" Proceedings of International Conference on Next Generation Computing Systems (ICNGCS - 2021), ISBN: 978 - 93 - 89515 - 35 - 0
18. N. Karthika and B. Sargunam, ‘YOLOv4 for Multi-class Artefact Detection in Endoscopic Images,’ 2021 International 3rd International Conference on Signal Processing and Communication (ICPSC), 2021, pp. 73-77, DOI: 10.1109/ICSPC51351.2021.9451761
19. Dr. G. Padmavathi, Dr. D. Shanmugapriya and Ms. S. Asha, ‘A Framework for Improving the Accuracy with Different Sampling Techniques for Detection of Malicious Insider Threat IN Cloud’ presented in 5th International Joint Conference on Advances in Computational Intelligence (IJCACI 2021) and published in series “Algorithms for Intelligent Systems”, 2021, pp. 1-10
20. Bindu Vazhakkatte Thazhathethil, Utthra Balasubramaniam and Sharon Treesa Abraham, "Coimbatore Destination Chatbot: A Study on Customer Preference," 2021 IoT Vertical and Topical Summit for Tourism, 2021, pp. 1-6, DOI: 10.1109/IEEECONF49204.2021.9604846
1.R Chakkaravarthini, SN Geethalakshmi, P Subashini and TT Dhivyaprabha. Digital Apps for Nursing the Health Conditions of Pregnant Women, Infants and Young Children. ScienceOpen Posters. 2023. DOI: https://doi.org/10.14293/P2199-8442.1.SOP-.PUWWLN.v1.
2.Pooja Sri Saraswathi A, Vijayabhanu R, Subashini P, Dhivyaprabha TT and Jennyfer Susan MB. Graph Neural Network: The Next Frontier in Deep Learning. ScienceOpen Posters. 2023. DOI: https://doi.org/10.14293/P2199-8442.1.SOP-.P9BKIX.v1.
3.Kamalini D, Vijayabhanu R, Subashini P, Dhivyaprabha TT and Jennyfer Susan MB. Revolutionizing Chemistry with Artificial Intelligence: Opportunities and Applications. ScienceOpen Posters. 2023. DOI: https://doi.org/10.14293/P2199-8442.1.SOP-.PSNSPU.v1.
4.Subashini, P., Krishnaveni, M., Dhivyaprabha, T.T., Malini, R., Keerthika, V., Kaviya, G. (2023). A contemporary study on solar energy applications and evaluation in real-time environment. International Poster Challenger Competition Peeref (Poster), DOI: https://doi.org/10.54985/peeref.2304p8181720.
scrolling test
teststs
test content for department
