Computing, Communication and Intelligence
1st Edition
Published on 15. April 2026
Book
Hardback
370 pages
978-1-041-28814-5 (ISBN)
Description
The Internet of things (IoT), Data Science, Robotics, Cloud Computing, etc., with Artificial Intelligence are the system of interconnected computing devices, objects such as machine, animals or people with Big Data and Intelligence are the ability to handle and communicate the data over a network for different real-time activities in this current era. Computing is being transformed to a model consisting of services that are commoditized and delivered in a manner similar to utilities. It leads to generates huge numbers of structure and unstructured data. Therefore, Enterprise and Big-Data applications need tools and platforms for their rapid construction and deployment on Clouds on-demand meeting user QoS requirements at lower price. This also helps in automation of the system in industry through Science and Technology and Engineering like; Instrumentation, IT, Mechatronic, Telecommunication, Electrical, among few others. In this regard, the International Conference on Cutting-edge Technology in Computing, Communication and Intelligence (ICCTCCI-2025) focuses on the application of smart technology and materials for smarter industrial production. The ICCTCCI-2025 will provide common platform for presentation of original research findings, exchange of ideas and dissemination of innovative, practical development experiences in different aspects and fields of industry. It also focuses event organized with the objective of bringing together academicians, scientists, researchers from industry, research scholars, and students working in different industrial domains and applied applications.
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Srinivas Sethi | Bibhudatta Sahoo | Deepak Tosh
Computing, Communication and Intelligence
Book
05/2026
1st Edition
CRC Press
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Srinivas Sethi | Bibhudatta Sahoo | Deepak Tosh
Computing, Communication and Intelligence
E-Book
04/2026
1st Edition
Taylor & Francis
€73.99
Available for download
Srinivas Sethi | Bibhudatta Sahoo | Deepak Tosh
Computing, Communication and Intelligence
E-Book
04/2026
1st Edition
Taylor & Francis
€73.99
Available for download
Persons
Srinivas Sethi
Prof. Srinivas Sethi is a professor in Computer Science Engineering & Application, Indira Gandhi Institute of Technology, Sarang (IGIT, Sarang), India, and has been actively involved in teaching and research since 1997. He did his Ph.D. in the area of routing algorithms in mobile ad hoc network and is continuing his research work in the wireless sensor network, cognitive radio network, cloud computing, BCI, and Cognitive Science. He is a member of the Editorial Board for different journal and program committee members for different international conferences/ workshops. He is book editor of 4 international conference proceedings published in Springer and Taylor & Francis. He has published more than 100 research papers in international journals, edited book chapters, and conference proceedings. He also published 2 nos. of Books. He completed 8 numbers of research and consultancy projects funded by different funding agencies such as DRDO, DST, AICTE, NPIU, and local Govt. office.
Bibhudatta Sahoo
Prof. Bibhudatta Sahoo is a computer science professor at NIT Rourkela, India, specializing in Algorithmic Engineering, Distributed Systems, Cloud Computing, Fog/Edge Computing & IoT, and Software Defined Networks/NFV. With a wealth of knowledge and expertise in these areas, Prof. Sahoo is at the forefront of cutting-edge research and innovation. Their research focuses on developing efficient algorithms and designing scalable distributed systems to address the challenges posed by modern computing paradigms such as cloud computing, fog/edge computing, and IoT. Driven by a passion for advancing the field, they have significantly contributed to developing software-defined networks and network function virtualization. Through their research, publications, and mentorship, Prof. Sahoo has inspired and empowered countless students, fostering a new generation of computer scientists equipped with the skills to tackle complex problems in the rapidly evolving world of technology.
Deepak Tosh
Prof. Deepak Tosh (Senior Member, IEEE) is an assistant professor of Computer Science at the University of Texas at El Paso. His research focuses on addressing various multi-disciplinary networking and cybersecurity challenges associated to critical national infrastructures, Industrial Internet of Things, Blockchain, and tactical battlefields. He works closely with researchers from U.S. Air Force Research Laboratory (AFRL), Sandia National Lab, and Army Research Laboratory (ARL) on developing resilient data/process provenance mechanisms for industrial operational technology environments, and military applications. His research has been funded from Department of Energy, National Science Foundation (NSF), and Department of Defense. He has authored/co-authored more than 70 peer-reviewed conference papers, book chapters, and journal papers. Two of his research works on Blockchain were also awarded as "Top 50 Blockchain Papers in 2018" at Block chain Connect Conference, 2019. He is also a recipient of prestigious NSF CAREER award, 2022.
Suvendra Kumar Jayasingh
Dr. Suvendra Kumar Jayasingh is working as Associate Professor and HOD in the Department of Computer Science & Engineering, Institute of Management and Information Technology (IMIT), Cuttack (A Constituent College of BPUT, Govt. of Odisha) after being selected by OPSC (Orissa Public Service Commission) in 2005. He has obtained his Bachelor of Engineering in the year 2003 from University College of Engineering (UCE), Burla (Now VSSUT). He got his M. Tech. in Computer Science & Engineering in 2007 from RVU, Udaipur and Ph. D. in Computer Science & Engineering in 2020 from North Orissa University, Baripada. He is having more than 20 years of teaching experience in Computer Science & Engineering and MCA. He has published several articles, book chapters in reputed National and International journals and periodicals including Springer and Taylor & Francis and has presented research papers in National and International Seminars and Conferences. He has organized many National and International Conferences and FDPs in collaboration with IITs, NITs and NITTTRs. His research interests include Artificial Intelligence, Data Mining, Soft Computing, Machine Learning, Computational Intelligence, Database Management System and Algorithm Analysis and Design. He has published book on "Introduction to Machine Learning", by Taran Publication, New Delhi, edited books on "Computing, Communication and Intelligence", "Intelligent Computing Techniques and Applications" by CRC Press, Taylor & Francis, UK patent on "Smart Home Air Quality Monitoring Device" and Indian Patent on "AI based Diary Products Testing Device". He is a life member of Indian Society for Technical Education (ISTE).
Sourav Kumar
Bhoi Prof. Sourav Kumar Bhoi (Sr. Member, IEEE and Member, ACM) completed his Doctoral (2017) and M. Tech. (2013) degrees from Department of Computer Science and Engineering, National Institute of Technology (NIT), Rourkela, India respectively. He completed his B. Tech (2011) from Dept. of CSE, Veer Surendra Sai University of Technology, Burla India. He completed his PDF (2023) research work from Srinivas University, India in CS&IS programme. He is currently working as Assistant Professor since 2016 in Dept. of CSE, Parala Maharaja Engineering College (a Govt. college affiliated to BPUT), Berhampur, India. His research interest includes Vehicular Networks, Internet of Things, Edge and Fog Computing, Machine Learning, and Information Security. He has nearly 10 years of teaching and research experience. He published nearly 130+ research publications in reputed International Journals and Conferences. He published 09 books/book chapters as author/co-author and 03 Indian Patents. He received nearly 10+ State/National/ International Awards for his research works such as prestigious IET Premium Award 2016, India Book of Record Holder 2022, BPUT-University Faculty Research Award 2021, ISTE-Rajalaxmi Award for Best Engineering College Teacher Award of Odisha State 2022, Institution of Engineers (IEI)-Sadananda Memorial Award 2021, Institution of Engineers (IEI)-JN Panda Memorial Award 2024, PDF Researcher with Good performance Award 2023, etc. He also completed one MHRD, Govt. of India research project on Smart Irrigation & continuing with one Project of AICTE, Govt. of India. He also acts as reviewer for many reputed organizations such as IEEE, IET, Elsevier, Springer, MDPI, Hindawi, Wiley, Taylor and Francis, etc. He guided nearly 80+ B.Tech students, 03 PG students, 01 PhD scholar awarded with Ph.D. degree, and currently guiding 03 Ph.D. scholars in new recent areas of Computer Sci. and Engg. He also acts as Faculty In-charge/Member of many administrative level sections/committees at institute and dept.
Prof. Srinivas Sethi is a professor in Computer Science Engineering & Application, Indira Gandhi Institute of Technology, Sarang (IGIT, Sarang), India, and has been actively involved in teaching and research since 1997. He did his Ph.D. in the area of routing algorithms in mobile ad hoc network and is continuing his research work in the wireless sensor network, cognitive radio network, cloud computing, BCI, and Cognitive Science. He is a member of the Editorial Board for different journal and program committee members for different international conferences/ workshops. He is book editor of 4 international conference proceedings published in Springer and Taylor & Francis. He has published more than 100 research papers in international journals, edited book chapters, and conference proceedings. He also published 2 nos. of Books. He completed 8 numbers of research and consultancy projects funded by different funding agencies such as DRDO, DST, AICTE, NPIU, and local Govt. office.
Bibhudatta Sahoo
Prof. Bibhudatta Sahoo is a computer science professor at NIT Rourkela, India, specializing in Algorithmic Engineering, Distributed Systems, Cloud Computing, Fog/Edge Computing & IoT, and Software Defined Networks/NFV. With a wealth of knowledge and expertise in these areas, Prof. Sahoo is at the forefront of cutting-edge research and innovation. Their research focuses on developing efficient algorithms and designing scalable distributed systems to address the challenges posed by modern computing paradigms such as cloud computing, fog/edge computing, and IoT. Driven by a passion for advancing the field, they have significantly contributed to developing software-defined networks and network function virtualization. Through their research, publications, and mentorship, Prof. Sahoo has inspired and empowered countless students, fostering a new generation of computer scientists equipped with the skills to tackle complex problems in the rapidly evolving world of technology.
Deepak Tosh
Prof. Deepak Tosh (Senior Member, IEEE) is an assistant professor of Computer Science at the University of Texas at El Paso. His research focuses on addressing various multi-disciplinary networking and cybersecurity challenges associated to critical national infrastructures, Industrial Internet of Things, Blockchain, and tactical battlefields. He works closely with researchers from U.S. Air Force Research Laboratory (AFRL), Sandia National Lab, and Army Research Laboratory (ARL) on developing resilient data/process provenance mechanisms for industrial operational technology environments, and military applications. His research has been funded from Department of Energy, National Science Foundation (NSF), and Department of Defense. He has authored/co-authored more than 70 peer-reviewed conference papers, book chapters, and journal papers. Two of his research works on Blockchain were also awarded as "Top 50 Blockchain Papers in 2018" at Block chain Connect Conference, 2019. He is also a recipient of prestigious NSF CAREER award, 2022.
Suvendra Kumar Jayasingh
Dr. Suvendra Kumar Jayasingh is working as Associate Professor and HOD in the Department of Computer Science & Engineering, Institute of Management and Information Technology (IMIT), Cuttack (A Constituent College of BPUT, Govt. of Odisha) after being selected by OPSC (Orissa Public Service Commission) in 2005. He has obtained his Bachelor of Engineering in the year 2003 from University College of Engineering (UCE), Burla (Now VSSUT). He got his M. Tech. in Computer Science & Engineering in 2007 from RVU, Udaipur and Ph. D. in Computer Science & Engineering in 2020 from North Orissa University, Baripada. He is having more than 20 years of teaching experience in Computer Science & Engineering and MCA. He has published several articles, book chapters in reputed National and International journals and periodicals including Springer and Taylor & Francis and has presented research papers in National and International Seminars and Conferences. He has organized many National and International Conferences and FDPs in collaboration with IITs, NITs and NITTTRs. His research interests include Artificial Intelligence, Data Mining, Soft Computing, Machine Learning, Computational Intelligence, Database Management System and Algorithm Analysis and Design. He has published book on "Introduction to Machine Learning", by Taran Publication, New Delhi, edited books on "Computing, Communication and Intelligence", "Intelligent Computing Techniques and Applications" by CRC Press, Taylor & Francis, UK patent on "Smart Home Air Quality Monitoring Device" and Indian Patent on "AI based Diary Products Testing Device". He is a life member of Indian Society for Technical Education (ISTE).
Sourav Kumar
Bhoi Prof. Sourav Kumar Bhoi (Sr. Member, IEEE and Member, ACM) completed his Doctoral (2017) and M. Tech. (2013) degrees from Department of Computer Science and Engineering, National Institute of Technology (NIT), Rourkela, India respectively. He completed his B. Tech (2011) from Dept. of CSE, Veer Surendra Sai University of Technology, Burla India. He completed his PDF (2023) research work from Srinivas University, India in CS&IS programme. He is currently working as Assistant Professor since 2016 in Dept. of CSE, Parala Maharaja Engineering College (a Govt. college affiliated to BPUT), Berhampur, India. His research interest includes Vehicular Networks, Internet of Things, Edge and Fog Computing, Machine Learning, and Information Security. He has nearly 10 years of teaching and research experience. He published nearly 130+ research publications in reputed International Journals and Conferences. He published 09 books/book chapters as author/co-author and 03 Indian Patents. He received nearly 10+ State/National/ International Awards for his research works such as prestigious IET Premium Award 2016, India Book of Record Holder 2022, BPUT-University Faculty Research Award 2021, ISTE-Rajalaxmi Award for Best Engineering College Teacher Award of Odisha State 2022, Institution of Engineers (IEI)-Sadananda Memorial Award 2021, Institution of Engineers (IEI)-JN Panda Memorial Award 2024, PDF Researcher with Good performance Award 2023, etc. He also completed one MHRD, Govt. of India research project on Smart Irrigation & continuing with one Project of AICTE, Govt. of India. He also acts as reviewer for many reputed organizations such as IEEE, IET, Elsevier, Springer, MDPI, Hindawi, Wiley, Taylor and Francis, etc. He guided nearly 80+ B.Tech students, 03 PG students, 01 PhD scholar awarded with Ph.D. degree, and currently guiding 03 Ph.D. scholars in new recent areas of Computer Sci. and Engg. He also acts as Faculty In-charge/Member of many administrative level sections/committees at institute and dept.
Content
1. Hybrid Social Spider and Grey Wolf Optimization for Enhanced Lifetime in
Wireless Sensor Network
2. A Comparative Study of Explainable Artificial Intelligence Algorithms in Local
Interpretable Model-Agnostic based Pneumonia Prediction
3. HERPEE: Hybrid Energy-Aware Routing Protocol with Energy Estimation in
IoT-Based Sensor Networks
4. High-Accuracy Face Mask Detection in Nuclear Environments using Ensemble
Learning and XGBoost
5. Contouring the Images of Lung Cancer Detection using CNN
6. Improving the Accuracy of Used Car Price Prediction Using Machine Learning Models
7. Leveraging Fractal Patterns in Machine Intelligence to Classify Brain Tumor Imaging
8. An Extreme Gradient Boosting Based Automated Software Defect Prediction Model Using
Dimensionality Reduction Technique
9. Optimum Rectangular Dielectric Resonator Antenna for Sub-6GHz in Rapid 5G
Communication Networks
10. Load Balancing in Cloud Computing Using Modified ANT Colony Algorithm
11. A Case Study of the Application of Deep Learning to Detect Skin Cancer
12. Machine Learning Approach for Image Caption Generation
13. Intelligent System for Corrosion Detection and Prediction System Using Deep Learning
14. Decentralized Brain Tumor Detection using Transfer Learning in Federated Frameworks
15. IoT based Anti-Collision Devices for Indian Railway: Insights to Implications
16. Deep Learning Based Face Recognition System with Modified MTCNN and FaceNet
17. Developing Encryption Strategies and Key Management Protocols that Ensure Security in
Dynamic Graph Networks through the Utilization of Asymmetric Cryptography
18. Advanced Wearable Sensors for Early Parkinson's Disease Tremor Detection using
Accelerometers and Gyroscopes
19. Enhancing MNIST Digit Classification Through Integrated Machine Learning and XAI
Approaches
20. Predicting Heart Disease using High Utility Itemsets Mining with an Enhanced Swarm
Intelligence Model 96
21. New Era of Pre Computation for Big Data Handling with Graph and Vector Databases
22. Harmony AI: A Web-Based ML Model for Hand Sign Language Translation
23. Implementation of Super AI in the Automation of Examination System for Academic
Enrichment: A Complete Learning for Tomorrow
24. Bio-Inspired Real-Time Facial Emotion Detection using Yolov11
25. Time-Series based Drug Efficiency and Side-Effect Prediction: Leveraging Machine
Learning for Enhanced Drug Safety and Personalized Medicine
26. Intelligent Systems with Cloud IoT Integration: A Synergistic Approach for Enhanced
Decision-Making
27. Leveraging AI for Enhanced Credit Scoring in Financial Services
28. Enhanced Dermoscopic Image Analysis for Skin Cancer Detection Using Transfer Learning
29. Smart Intelli Secure-Based LPG and Fire Safety System with Automatic Door Control
30. Convolutional Neural Network Approach for Grape Leaf Disease Classification
31. High-Efficiency Optical Polarizer using Silicon based 2D Device for Photonic
Integrated Circuits
32. GPT-4-Powered Medical Recommendation System using SNOMED
33. Deep Q-Network-Based Self-Healing for Enhanced UE Experience in 5G Networks
34. Machine Learning Applications in Predicting the Disease Progression in Diabetes Patients:
A Comprehensive Exploration
35. A Crop Recommendation System with High Accuracy Utilizing Ensemble Machine
Learning Techniques
36. Leveraging Transfer Learning for Enhanced Handwritten Digit Recognition using
EfficientNet and Fine-Tuned CNN
37. Efficient Task Scheduling Algorithm Based Load Balancing in Cloud Computing
38. Automation in Healthcare: A Robotic Approach for Patient Registration, Vital Sign
Tracking, and Chatbot Interaction
39. Energy Optimization of LoRa Networks of Smart Building using Machine Learning
40. Characterizing Serverless Workloads in Production
41. SMOTETomek Enriched GWO: A Hybrid Approach for Diabetes Disease Prediction
42. Utilizing Machine Learning to Enhance Agronomic Practices and Crop Yield Prediction
43. Lung Cancer Detection using Machine Learning: A Comprehensive Approach with
Logistic Boosting Model Accuracy
44. IoT Assisted Novel Anti-Collision Warning System for Indian Heavy Commercial Vehicles
45. A Systematic Review of Computational Intelligence Approaches for Improving
Communication and Security in Vehicular Adhoc Networks
46. Harnessing LSTM Networks for Predictive Analysis in Stock Market Dynamics
47. Harnessing Deep Learning and Transfer Learning for Gemstone Classification and
Authenticity Analysis
48. Advancing Land Use and Land Cover Classification Through Deep Learning in
Satellite Imagery
49. Deep Learning Based Classification of Bone Fracture: A Vision Transformer-CNN Approach
50. Multi-Class Disease Detection for Sugarcane Leaf using CNN and Transfer Learning Approach
51. Identification of Key Environmental Factors Affecting Atmospheric Corrosion of
Mild Steel Using Machine Learning Techniques
52. Integrating CNNs and Vision Transformers for Enhanced Pneumonia Detection in
Radiographic Images
53. Enhanced Food Quality Detection using CNN Architectures
54. ABC-LNN: A Hybrid Task Scheduling and Load Balancing Approach Leveraging
Artificial Bee Colony with Liquid Neural Networks in Cloud Computing
55. Energy Efficiency in Wireless Sensor-based Internet of Things: An Experimental Analysis
56. Transfer Learning based ResNet50 Model for Emotion Detection
57. Evaluating the Performance of RCNN Variants for Multi-Object Analysis in Images
58. Encoded Feature Fusion-Based Pneumonia Detection using Ensemble Federated Approach
59. IoT-integrated Water Quality Surveillance and Smart Feeding for High-Density Pisciculture
Sustainability
60. Enhancing Cardiovascular Risk Prediction with Optimal Performance of Random
Gradient Ensemble Model
61. Inertia Weight Strategies with Time Variations in PSO-based Cloud Task Scheduling
Algorithm
62. AI-Powered Digital Signages Management System: A Revolution in Digital Marketing
63. A Particle Swarm Optimization Based Neural Network Model for Tourism
Machination System
64. Neuralink Unleashed: Navigating the Intersections of Technology, Humanity, and Nature
65. Predication of Solar Still Production Rate using Artificial Neural Network and Step
Regression Model
66. A Blockchain Enable Technology for IoT Based Applications for Enhancing the
Security and Transparency
67. Heart Stroke Prediction Using Machine Learning Approach with Clinical and
Demographic Factors
68. Malaria Detection from Blood Smears Using Deep Learning Frameworks
69. Deep Learning-Based Stock Forecasting and Recommendation System using a Hybrid
TCN-LSTM Approach Incorporating Fundamental and Technical Analysis
Wireless Sensor Network
2. A Comparative Study of Explainable Artificial Intelligence Algorithms in Local
Interpretable Model-Agnostic based Pneumonia Prediction
3. HERPEE: Hybrid Energy-Aware Routing Protocol with Energy Estimation in
IoT-Based Sensor Networks
4. High-Accuracy Face Mask Detection in Nuclear Environments using Ensemble
Learning and XGBoost
5. Contouring the Images of Lung Cancer Detection using CNN
6. Improving the Accuracy of Used Car Price Prediction Using Machine Learning Models
7. Leveraging Fractal Patterns in Machine Intelligence to Classify Brain Tumor Imaging
8. An Extreme Gradient Boosting Based Automated Software Defect Prediction Model Using
Dimensionality Reduction Technique
9. Optimum Rectangular Dielectric Resonator Antenna for Sub-6GHz in Rapid 5G
Communication Networks
10. Load Balancing in Cloud Computing Using Modified ANT Colony Algorithm
11. A Case Study of the Application of Deep Learning to Detect Skin Cancer
12. Machine Learning Approach for Image Caption Generation
13. Intelligent System for Corrosion Detection and Prediction System Using Deep Learning
14. Decentralized Brain Tumor Detection using Transfer Learning in Federated Frameworks
15. IoT based Anti-Collision Devices for Indian Railway: Insights to Implications
16. Deep Learning Based Face Recognition System with Modified MTCNN and FaceNet
17. Developing Encryption Strategies and Key Management Protocols that Ensure Security in
Dynamic Graph Networks through the Utilization of Asymmetric Cryptography
18. Advanced Wearable Sensors for Early Parkinson's Disease Tremor Detection using
Accelerometers and Gyroscopes
19. Enhancing MNIST Digit Classification Through Integrated Machine Learning and XAI
Approaches
20. Predicting Heart Disease using High Utility Itemsets Mining with an Enhanced Swarm
Intelligence Model 96
21. New Era of Pre Computation for Big Data Handling with Graph and Vector Databases
22. Harmony AI: A Web-Based ML Model for Hand Sign Language Translation
23. Implementation of Super AI in the Automation of Examination System for Academic
Enrichment: A Complete Learning for Tomorrow
24. Bio-Inspired Real-Time Facial Emotion Detection using Yolov11
25. Time-Series based Drug Efficiency and Side-Effect Prediction: Leveraging Machine
Learning for Enhanced Drug Safety and Personalized Medicine
26. Intelligent Systems with Cloud IoT Integration: A Synergistic Approach for Enhanced
Decision-Making
27. Leveraging AI for Enhanced Credit Scoring in Financial Services
28. Enhanced Dermoscopic Image Analysis for Skin Cancer Detection Using Transfer Learning
29. Smart Intelli Secure-Based LPG and Fire Safety System with Automatic Door Control
30. Convolutional Neural Network Approach for Grape Leaf Disease Classification
31. High-Efficiency Optical Polarizer using Silicon based 2D Device for Photonic
Integrated Circuits
32. GPT-4-Powered Medical Recommendation System using SNOMED
33. Deep Q-Network-Based Self-Healing for Enhanced UE Experience in 5G Networks
34. Machine Learning Applications in Predicting the Disease Progression in Diabetes Patients:
A Comprehensive Exploration
35. A Crop Recommendation System with High Accuracy Utilizing Ensemble Machine
Learning Techniques
36. Leveraging Transfer Learning for Enhanced Handwritten Digit Recognition using
EfficientNet and Fine-Tuned CNN
37. Efficient Task Scheduling Algorithm Based Load Balancing in Cloud Computing
38. Automation in Healthcare: A Robotic Approach for Patient Registration, Vital Sign
Tracking, and Chatbot Interaction
39. Energy Optimization of LoRa Networks of Smart Building using Machine Learning
40. Characterizing Serverless Workloads in Production
41. SMOTETomek Enriched GWO: A Hybrid Approach for Diabetes Disease Prediction
42. Utilizing Machine Learning to Enhance Agronomic Practices and Crop Yield Prediction
43. Lung Cancer Detection using Machine Learning: A Comprehensive Approach with
Logistic Boosting Model Accuracy
44. IoT Assisted Novel Anti-Collision Warning System for Indian Heavy Commercial Vehicles
45. A Systematic Review of Computational Intelligence Approaches for Improving
Communication and Security in Vehicular Adhoc Networks
46. Harnessing LSTM Networks for Predictive Analysis in Stock Market Dynamics
47. Harnessing Deep Learning and Transfer Learning for Gemstone Classification and
Authenticity Analysis
48. Advancing Land Use and Land Cover Classification Through Deep Learning in
Satellite Imagery
49. Deep Learning Based Classification of Bone Fracture: A Vision Transformer-CNN Approach
50. Multi-Class Disease Detection for Sugarcane Leaf using CNN and Transfer Learning Approach
51. Identification of Key Environmental Factors Affecting Atmospheric Corrosion of
Mild Steel Using Machine Learning Techniques
52. Integrating CNNs and Vision Transformers for Enhanced Pneumonia Detection in
Radiographic Images
53. Enhanced Food Quality Detection using CNN Architectures
54. ABC-LNN: A Hybrid Task Scheduling and Load Balancing Approach Leveraging
Artificial Bee Colony with Liquid Neural Networks in Cloud Computing
55. Energy Efficiency in Wireless Sensor-based Internet of Things: An Experimental Analysis
56. Transfer Learning based ResNet50 Model for Emotion Detection
57. Evaluating the Performance of RCNN Variants for Multi-Object Analysis in Images
58. Encoded Feature Fusion-Based Pneumonia Detection using Ensemble Federated Approach
59. IoT-integrated Water Quality Surveillance and Smart Feeding for High-Density Pisciculture
Sustainability
60. Enhancing Cardiovascular Risk Prediction with Optimal Performance of Random
Gradient Ensemble Model
61. Inertia Weight Strategies with Time Variations in PSO-based Cloud Task Scheduling
Algorithm
62. AI-Powered Digital Signages Management System: A Revolution in Digital Marketing
63. A Particle Swarm Optimization Based Neural Network Model for Tourism
Machination System
64. Neuralink Unleashed: Navigating the Intersections of Technology, Humanity, and Nature
65. Predication of Solar Still Production Rate using Artificial Neural Network and Step
Regression Model
66. A Blockchain Enable Technology for IoT Based Applications for Enhancing the
Security and Transparency
67. Heart Stroke Prediction Using Machine Learning Approach with Clinical and
Demographic Factors
68. Malaria Detection from Blood Smears Using Deep Learning Frameworks
69. Deep Learning-Based Stock Forecasting and Recommendation System using a Hybrid
TCN-LSTM Approach Incorporating Fundamental and Technical Analysis