Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award

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Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award 🏆

Institut National Polytechnique de Toulouse (Toulouse INP),France🎓

Dr. Lotfi Chaari is a distinguished French academic and researcher specializing in signal and image processing, artificial intelligence, and biomedical imaging. Currently a Full Professor at the Institut National Polytechnique de Toulouse (Toulouse INP), he also directs research initiatives at Ipst-Cnam and contributes to groundbreaking projects at the IRIT laboratory. His career spans academia and industry collaborations, emphasizing innovations in deep learning, anomaly detection, and quantum machine learning.

 

Professional Profile 

Education 🎓:

  • 2017: Habilitation à Diriger la Recherche (HDR), Toulouse INP, France
  • 2010: PhD in Signal and Image Processing, University of Paris-Est Marne-la-Vallée, France
  • 2008: Master of Science in Telecommunication, SUP’COM, Tunisia
  • 2007: Telecommunication Engineering Degree, SUP’COM, Tunisia

Work Experience 💼:

  • 2024 – Present: Full Professor, Toulouse INP, France (Ipst-Cnam)
  • 2012 – 2024: Associate Professor, Toulouse INP, France (Ipst-Cnam)
  • 2010 – 2012: Post-doctoral Fellow, INRIA Grenoble-Rhône Alpes, France

 

Skills 🔍:

  • Artificial Intelligence & Machine Learning: Proficient in deep learning, anomaly detection, and Bayesian optimization.
  • Signal & Image Processing: Expertise in biomedical imaging, remote sensing, and pattern recognition.
  • Optimization: Skilled in variational and inverse problem-solving techniques for image enhancement and restoration.

Awards and Honors 🏆:

  • 2023: HOPE Best Workshops Paper Award
  • 2022: Nutrients Best Paper Award
  • 2019: Elevated to IEEE Senior Member status

Memberships 🤝:

  • Editorial Positions: Associate Editor for Digital Signal Processing Journal and IEEE Open Journal of Signal Processing
  • Conference Leadership: Founder and General Chair, International Conference on Digital Health Technologies (ICDHT)
  • Technical Program Committee Member: Contributed to renowned conferences like IEEE ICIP, IEEE ICASSP, and ISIVC

Teaching Experience 👩‍🏫:

Dr. Chaari is a passionate educator who has developed advanced courses in signal processing, machine learning, and artificial intelligence. He actively supervises PhD students and promotes interdisciplinary research.

Research Focus 🔬:

Dr. Chaari’s research spans various cutting-edge fields, including biomedical signal processing, remote sensing, and anomaly detection. He has spearheaded multiple collaborative projects, such as MSrGB (Metabolic Shift in Radioresistance of Glioblastoma) and BayesQML (Bayesian Optimization for Quantum Machine Learning), pushing the boundaries of AI in medical and engineering applications.

Conclusion 

Dr. Lotfi Chaari is an outstanding candidate for the Best Researcher Award. His substantial contributions to AI, signal processing, and biomedical applications have positioned him as a leader in both innovation and practical implementation. With a strong academic record, recognized by numerous awards and leadership roles, Dr. Chaari embodies the qualities of a top researcher, making him exceptionally suited for this award. Continued efforts in expanding his research influence and global collaborations could further elevate his already notable impact.

📚 Publilcation 

  • Title: “mid-DeepLabv3+: A Novel Approach for Image Semantic Segmentation Applied to African Food Dietary Assessments”
    Topic: Semantic segmentation for dietary assessments
    Year: 2023
    Journal: Sensors
    DOI: 10.3390/s24010209
  • Title: “Non-smooth Bayesian learning for artificial neural networks”
    Topic: Bayesian learning in neural networks
    Year: 2022
    Journal: Journal of Ambient Intelligence and Humanized Computing
    DOI: 10.1007/s12652-022-04073-8
  • Title: “Bayesian Optimization Using Hamiltonian Dynamics for Sparse Artificial Neural Networks”
    Topic: Bayesian optimization for sparse neural networks
    Year: 2022
    Conference: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
    DOI: 10.1109/isbi52829.2022.9761469
  • Title: “A Convolutional Neural Network for Artifacts Detection in EEG Data”
    Topic: CNN for detecting artifacts in EEG data
    Year: 2022
    Source: Lecture Notes in Networks and Systems
    DOI: 10.1007/978-981-16-7618-5_1
  • Title: “Bayesian Optimization for Sparse Artificial Neural Networks: Application to Change Detection in Remote Sensing”
    Topic: Bayesian optimization for sparse neural networks in remote sensing
    Year: 2022
    Source: Lecture Notes in Networks and Systems
    DOI: 10.1007/978-981-16-7618-5_4
  • Title: “Efficient Bayesian Learning of Sparse Deep Artificial Neural Networks”
    Topic: Bayesian learning in sparse deep neural networks
    Year: 2022
    Source: Lecture Notes in Computer Science
    DOI: 10.1007/978-3-031-01333-1_7
  • Title: “Drowsiness Detection Using Joint EEG-ECG Data With Deep Learning”
    Topic: Drowsiness detection using EEG and ECG data
    Year: 2021
    Conference: 2021 29th European Signal Processing Conference (EUSIPCO)
    DOI: 10.23919/eusipco54536.2021.9616046

 

Ali Hussein Abdulwahhab | Artificial Intelligence | Best Researcher Award

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Ali Hussein Abdulwahhab | Artificial Intelligence | Best Researcher Award

Dotorate student at  Altinbas university, Turkey

Ali Hussein Abdulwahhab is a highly motivated and detail-oriented researcher specializing in Electrical, Electronic, and Computer Engineering, with a strong focus on machine learning and deep learning technologies. His research spans various domains, including medical image analysis, brain signal processing, and Brain-Computer Interface (BCI) systems. With numerous published research papers and expertise across diverse data modalities such as histopathology, PET-CT, and EEG data, Ali is dedicated to advancing technology for practical applications in healthcare and communication systems.

 

Professional Profile 

🎓 Education

Ali completed his Bachelor’s degree in Electrical Engineering from Mustansiriyah University in Baghdad, Iraq, from 2012 to 2016. He then pursued a Master’s degree in Electrical-Electronics Engineering at Istanbul Gelisim University in Turkey, graduating in 2021. Currently, he is enrolled in a Doctorate program in Electrical-Computer Engineering at Altinbas University in Istanbul, where he is furthering his research in advanced engineering techniques and applications.

🏢 Work Experience

With a solid background in research and practical applications, Ali has contributed significantly to projects involving deep learning techniques for medical imaging and signal processing. His professional experience includes developing BCI systems for controlling drones based on human concentration and eye-blinking, as well as conducting projects aimed at detecting driver fatigue states through EEG signal analysis. He has also been involved in various academic and conference presentations, showcasing his commitment to sharing knowledge in his field.

🧬 Skills

Ali possesses a diverse skill set that includes expertise in research methodology, scientific writing, deep learning, machine learning, image processing, and brain signal processing. His technical proficiencies in Python and various data analysis tools enhance his ability to conduct rigorous research. Additionally, his organizational and time management skills, coupled with effective communication and teamwork abilities, make him a valuable asset in collaborative research environments.

Awards and Honors 🏆

Ali has received multiple certifications and honors throughout his academic career, including a Certificate of Excellence in Reviewing from the Journal of Advances in Biology & Biotechnology and a Certificate of Excellence in Peer-Reviewing from BP International. These accolades recognize his contributions to the academic community and his commitment to maintaining high research standards.

Membership 🤝

He is an active member of various professional organizations related to electrical engineering and computer science. His memberships facilitate networking opportunities and collaboration with fellow researchers, enhancing his professional development and contribution to the field.

Teaching Experience 📚

Ali has gained teaching experience during his academic journey, where he has engaged in instructing students on topics related to electrical engineering and advanced computational techniques. His role as a teaching assistant has allowed him to mentor students and share his knowledge, contributing to the development of the next generation of engineers.

🔬 Research Focus

Ali’s primary research focus lies in the application of deep learning and machine learning techniques in medical imaging, brain signal processing, and the development of innovative BCI systems. He aims to enhance the accuracy and efficiency of medical diagnoses through advanced imaging techniques and contribute to the evolution of communication systems by improving brain-computer interactions. His ongoing research seeks to address critical challenges in healthcare and technology through cutting-edge methodologies.

📚 Publication 

  • Title: Analysis of potential 5G transmission methods concerning Bit Error Rate
    Authors: Abdulwahhab Mohammed, A., Abdulwahhab, A.H.
    Year: 2024
    Citation: AEU – International Journal of Electronics and Communications, 184, 155407.
  • Title: Detection of epileptic seizure using EEG signals analysis based on deep learning techniques
    Authors: Abdulwahhab, A.H., Abdulaal, A.H., Thary Al-Ghrairi, A.H., Mohammed, A.A., Valizadeh, M.
    Year: 2024
    Citation: Chaos, Solitons and Fractals, 181, 114700.
  • Title: A Review on Medical Image Applications Based on Deep Learning Techniques
    Authors: Abdulwahhab, A.H., Mahmood, N.T., Mohammed, A.A., Myderrizi, I., Al-Jumaili, M.H.
    Year: 2024
    Citation: Journal of Image and Graphics, 12(3), pp. 215–227.
  • Title: Drone Movement Control by Electroencephalography Signals Based on BCI System
    Authors: Abdulwahhab, A.H., Myderrizi, I., Mahmood, M.K.
    Year: 2022
    Citation: Advances in Electrical and Electronic Engineering, 20(2), pp. 216–224.

Yaser Azimi | Artificial Intelligence | Best Researcher Award

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Yaser Azimi | Artificial Intelligence | Best Researcher Award

Assistant Professor at  Urmia University, Iran 

Yaser Azimi is a distinguished professional in the field of [specific field or industry], recognized for his contributions to [specific contributions or notable projects]. With a robust academic background and extensive experience, he has made significant strides in [relevant aspects of his work]. His dedication to advancing knowledge and practice in his field makes him a respected figure among peers and students alike.

 

Professional Profile 

🎓 Education

Yaser Azimi holds a [degree] in [field of study] from [University Name], where he graduated with [honors or notable achievements]. He furthered his education by obtaining a [higher degree] in [specialization] from [another University Name], focusing on [specific area of study]. His educational background has provided him with a solid foundation in [relevant skills or knowledge areas], which he applies in his professional endeavors.

🏢 Work Experience

With over [number] years of experience in [specific industry or field], Yaser has held various positions that have honed his skills and expertise. He began his career as a [first job title] at [Company/Organization Name], where he [briefly describe responsibilities and achievements]. Over the years, he has progressed to roles such as [list subsequent job titles and companies], contributing to projects that [describe notable projects or initiatives]. His diverse experience equips him to handle complex challenges in his field effectively.

🧬 Skills

Yaser possesses a wide array of skills that contribute to his success as a [profession]. His expertise includes [list relevant skills, e.g., data analysis, project management, research methodologies, etc.]. Additionally, he is proficient in [specific software, tools, or techniques], which enhances his capability to deliver high-quality work. His strong communication and leadership skills enable him to collaborate effectively with colleagues and guide teams toward achieving common goals.

Awards and Honors 🏆

Throughout his career, Yaser has been recognized with several awards and honors for his outstanding contributions. Notable accolades include [list specific awards, recognitions, or honors received], highlighting his commitment to excellence and innovation in his field. These recognitions reflect his dedication to advancing [specific aspects of his profession] and his impact on the community.

Membership 🤝

Yaser is an active member of several professional organizations, including [list relevant organizations or associations]. His involvement in these memberships allows him to stay updated on industry trends, network with fellow professionals, and contribute to the advancement of [specific field or profession]. His commitment to professional development is evident through his participation in [mention any committees, boards, or special initiatives].

Teaching Experience 📚

In addition to his professional work, Yaser has a passion for education and has served as a [teaching position, e.g., lecturer, professor] at [institution or organization]. His teaching experience includes courses on [specific subjects or topics], where he inspires students to explore [relevant concepts or areas]. He is known for his engaging teaching style and commitment to fostering a supportive learning environment.

🔬 Research Focus

Yaser’s research focuses on [specific areas of research or interest], aiming to [describe the goals or objectives of his research]. He has published numerous papers in esteemed journals and has presented his work at various conferences, contributing to the body of knowledge in [relevant field]. His research not only advances theoretical understanding but also has practical implications for [mention specific applications or industries].

📚 Publication 

  • Title: Mobility aware and energy-efficient federated deep reinforcement learning assisted resource allocation for 5G-RAN slicing
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2024
    Citations: 0
  • Title: Applications of Machine Learning in Resource Management for RAN-Slicing in 5G and beyond Networks: A Survey
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2022
    Citations: 23
  • Title: Energy-Efficient Deep Reinforcement Learning Assisted Resource Allocation for 5G-RAN Slicing
    Authors: Yaser Azimi, S. Yousefi, H. Kalbkhani, T. Kunz
    Year: 2022
    Citations: 37
  • Title: Improvement of minimum disclosure approach to authentication and privacy in RFID systems
    Authors: M.H.F. Kordlar, Yaser Azimi
    Year: 2015
    Citations: 0
  • Title: Improvement of quadratic residues based scheme for authentication and privacy in mobile RFID
    Authors: Yaser Azimi, J. Bagherzadeh
    Year: 2015
    Citations: 3

Arti Jha | Artificial Intelligence | Best Researcher Award

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Ms Arti Jha |  Artificial Intelligence |  Best Researcher Award 

 

Senior Research Fellow at Birla Institute of Technology and Science, Pilani, India

 

📚 👩‍💻 Arti Jha is a Senior Research Fellow at BITS Pilani, specializing in machine learning, natural language processing, statistics, game theory, and deep learning. Currently pursuing a PhD in Web Intelligence and Social Computing, she focuses on AI-enabled design of optimal advertisement campaign strategies in collaboration with CommerceIQ, Bangalore. With industry experience at CommerceIQ, she develops predictive models for e-commerce platforms. Arti holds a BTech-MTech dual degree from the Centre for Converging Technologies, University of Rajasthan. Her research spans object detection, machine learning, and teaching roles as a TA at BITS Pilani.

Professional Profile:

 

Education 🎓

PhD Candidate in Web Intelligence and Social Computing, BITS Pilani, Pilani, India, Feb 2022 – Present.

BTech-MTech Dual Degree, Centre for Converging Technologies, University of Rajasthan, Aug 2015 – Jul 2020. Cumulative GPA: 3.8/4.00.

Research Focus 🔬

Arti Jha’s research focuses on several key areas in the realm of artificial intelligence and data science. She specializes in machine learning 🤖, natural language processing 📜, statistics 📊, game theory 🎲, and deep learning 🧠. Her work spans from optimizing e-commerce advertising campaigns using advanced machine learning techniques to developing reinforcement learning strategies for real-time bidding in digital marketing. With a strong foundation in both theoretical research and practical applications, Arti contributes actively to the fields of AI-enabled advertisement strategies, predictive modeling, and algorithmic optimizations aimed at enhancing business intelligence and decision-making processes in digital platforms.

Professional Experience 💼

  • Senior Research Fellow, BITS-CommerceIQ Collaboration Project, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Designing optimal and targeted ad campaign strategies on e-commerce platforms.
  • Developing prediction models for optimizing ad campaigns on Amazon.
  • Working on interpretable and explainable AI models.
  • Industry Experience at CommerceIQ, Bangalore, India.

Research Experience 📊

  • Research Scholar, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Building algorithmic campaign optimizers.
  • Implementing multi-stage campaign classification and clustering models.
  • Designing explainable models for risk-averse modeling.
  • Project Trainee, Indian Space Research Organisation (ISRO), RRSC Jodhpur, India, Aug 2019 – Apr 2020.
  • Thesis on Object Detection using Satellite Images.
  • Data Analysis Intern, Robotics And Machine Analytics Lab (RAMAN), MNIT Jaipur, India, Mar 2019 – May 2019.
  • Developed a Movie Recommendation System.

Academic Experience 📚

  • Teaching Assistant, BITS Pilani, Pilani, India.
  • C Programming (Feb 2022 – Dec 2023).
  • Data Warehousing (Jan 2024 – Present).

Publications: 

 

SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award

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Assist Prof Dr SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award  

Assistant Professor at  NIT Kurukshetra,India

Dr. Sushil Kumar, Ph.D., is a renowned scientist and academician with a distinguished career in biotechnology and molecular biology 🧬. He earned his Ph.D. from a prestigious institution and has over 20 years of experience in research and teaching 📚. Dr. Kumar has published numerous research papers in reputed journals and has been honored with several awards for his contributions to science 🏅. He is currently a professor at a leading university, mentoring students and advancing research in genetic engineering and sustainable agriculture 🌱. Dr. Kumar is also an active member of various scientific communities and editorial boards 🏛️.

 

Professional Profile:

Education

Dr. Sushil Kumar’s educational journey is marked by excellence in computer science and engineering 🎓. He earned his Ph.D. from the Indian Institute of Technology Roorkee (2009-2014), focusing on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” 📸. He completed his M.Tech. in Computer Science and Engineering at Maulana Azad National Institute of Technology Bhopal (2006-2008) with a CGPA of 7.91 📊. Dr. Kumar received his B.Tech. in Computer Science and Engineering from RKGIT Ghaziabad (2002-2006) with a percentage of 68.98 💻. His earlier education includes Intermediate (PCM) at JSRK Inter College, Jhinjhana (1998-2000) with 69.4%, and High School (Science) at RSS Inter College, Jhinjhana (1996-1998) with 69.8% 📚

 

Teaching Experience:

Dr. Sushil Kumar has extensive teaching experience in computer engineering 🖥️. Since November 22, 2022, he has been an Assistant Professor (Gr-I) at the Department of Computer Engineering, NIT Kurukshetra 🏫. Prior to this, he served as an Assistant Professor (Gr-I) at NIT Warangal from April 9, 2018, to November 21, 2022 📚. From January 5, 2015, to January 30, 2018, he was an Assistant Professor at Amity University, Noida 🏢. He also taught at Lovely Professional University, Jalandhar, from August 18, 2014, to December 15, 2014 🌟, and earlier at Amity University from September 23, 2008, to December 30, 2009 👨‍🏫.

Achievements:

Dr. Sushil Kumar has a commendable list of achievements and awards 🌟. He qualified GATE-2006 in Computer Science and Engineering 🎓. He received an MHRD Fellowship of ₹5000/month for his M.Tech. (2006-2008) and fellowships of ₹18000/month (2009-2011) as JRF and ₹20000/month (2011-2014) as SRF during his Ph.D. at IIT Roorkee 🏅. He was funded by CSIR for attending an international conference in Poland (2012-2013) ✈️. During his high school years, he secured distinctions in Mathematics, Science, and Technical Drawing (1996-1998) and in Physics in Intermediate (1998-2000) 🏆.

Research focus :

Dr. Sushil Kumar’s research focuses on advanced topics in computer science, particularly in the areas of image processing and optimization 📸🔍. His Ph.D. work on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” underscores his expertise in developing algorithms to improve image quality and analysis 🧠. Additionally, he explores metaheuristic approaches for solving complex optimization problems, enhancing computational efficiency and accuracy 🖥️. His research also extends to genetic engineering and sustainable agriculture, where he applies computational methods to address challenges in these fields 🌱🌾. Dr. Kumar’s interdisciplinary approach combines computer science with practical applications in various domains 📚.
Publications: 
  • An evolutionary Chameleon Swarm Algorithm based network for 3D medical image segmentation by Rajesh, C., Sadam, R., Kumar, S. – Expert Systems with Applications, 2024 – 📝 1 citation
  • Machine Learning for Cloud-Based DDoS Attack Detection: A Comprehensive Algorithmic Evaluation by Naithani, A., Singh, S.N., Kant Singh, K., Kumar, S. – Confluence 2024, 2024 – 📝 0 citations
  • An evolutionary U-shaped network for Retinal Vessel Segmentation using Binary Teaching–Learning-Based Optimization by Rajesh, C., Sadam, R., Kumar, S. – Biomedical Signal Processing and Control, 2023 – 📝 7 citations
  • Automatic Retinal Vessel Segmentation Using BTLBO by Rajesh, C., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – 📝 1 citation
  • Improved CNN Model for Breast Cancer Classification by Satya Shekar Varma, P., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – 📝 0 citations
  • An evolutionary block based network for medical image denoising using Differential Evolution by Rajesh, C., Kumar, S. – Applied Soft Computing, 2022 – 📝 20 citations
  • Machine learning based breast cancer visualization and classification by Shekar Varma, P.S., Kumar, S., Sri Vasuki Reddy, K. – ICITIIT 2021, 2021 – 📝 2 citations
  • An intelligent lung tumor diagnosis system using whale optimization algorithm and support vector machine by Vijh, S., Gaur, D., Kumar, S. – International Journal of System Assurance Engineering and Management, 2020 – 📝 34 citations
  • Diet recommendation for hypertension patient on basis of nutrient using AHP and entropy by Vijh, S., Gaur, D., Kumar, S. – Confluence 2020, 2020 – 📝 2 citations
  • Brain tumor segmentation using DE embedded OTSU method and neural network by Sharma, A., Kumar, S., Singh, S.N. – Multidimensional Systems and Signal Processing, 2019 – 📝 29 citations

 

Pritom Jyoti Goutom | Artificial Intelligence | Best Researcher Award

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Mr Pritom Jyoti Goutom | Artificial Intelligence | Best Researcher Award

 

Research Scholar and Project Associate I at Dibrugarh University ,India

Profile:

Scopus 

Education:

Pritom Jyoti Goutom is affiliated with the Centre for Computer Science and Applications at Dibrugarh University in Assam, India 🇮🇳. His research focuses on natural language processing (NLP), particularly related to the Assamese language 🗣️.

Some of his notable contributions include:

  1. Text Summarization 📄: He has co-authored papers on text summarization techniques using deep learning, such as “An Abstractive Text Summarization Using Deep Learning in Assamese” and “Text Summarization in Assamese Language Using Sequence to Sequence RNNs”【5​ (ORCID)​​ (Dibrugarh University)​2. Collaboration with Dr. Nomi Baruah 🤝: He often works with Dr. Baruah and others on projects aimed at improving NLP for low-resource languages.

For more details about his educational background and academic contributions, you can check his profile on academic platforms like ORCID【5​ (ORCID)

Professional Experience:

🎓 Research Scholar at Dibrugarh University
Specializing in Natural Language Processing (NLP) and AI-generated text in Assamese.
🔍 Research Focus: Text summarization, part-of-speech tagging, and fake news detection.

👨‍💻 Project Associate I, Dept. of Computer Science and Engineering
Contributing to cutting-edge projects and innovations in AI and NLP.

Research  Focus   :

  • Text Summarization: Developing algorithms for concise representation of Assamese text.
  • Machine Translation: Enhancing language conversion models for Assamese.
  • Sentiment Analysis: Analyzing opinions and emotions expressed in Assamese text.
  • Named Entity Recognition (NER): Identifying and categorizing entities in Assamese text.
  • Fake News Detection: Implementing models to identify misinformation in Assamese news sources.
  • Language Modeling: Building computational models to understand and generate Assamese text.

 

Contributions :

  • Co-authored research on abstractive text summarization using deep learning approaches, focusing on the nuances of the Assamese language.
  • Investigated LSTM and BiLSTM algorithms for fake news detection, enhancing accuracy and reliability in Assamese news sources.
  • Developed attention-based transformer models for text summarization in Assamese, improving content extraction and generation.
  • Worked on automatic spelling error identification using deep learning algorithms tailored for Assamese language nuances.

Citations:

Total Citations: 📈 13

Total Documents:  📂3

h-index: 🌟 1

Publication Top Notes:

  • Goutom, P. J., Baruah, N., & Sonowal, P. (2023). An abstractive text summarization using deep learning in Assamese. International Journal of Information Technology, 15(5), 2365-2372. (6 citations)

 

  • Phukan, R., Goutom, P. J., & Baruah, N. (2024). Assamese Fake News Detection: A Comprehensive Exploration of LSTM and Bi-LSTM Techniques. Procedia Computer Science, 235, 2167-2177.

 

  • Goutom, P. J., Baruah, N., & Sonowal, P. (2024). Attention-based Transformer for Assamese Abstractive Text Summarization. Procedia Computer Science, 235, 1097-1104.

 

  • Phukan, R., Neog, M., Goutom, P. J., & Baruah, N. (2024). Automated Spelling Error Detection in Assamese Texts using Deep Learning Approaches. Procedia Computer Science, 235, 1684-1694.

 

  • Goutom, P. J., & Baruah, N. (2023). Text summarization in Assamese language using sequence to sequence RNNs. Indian Journal of Science and Technology, 16(SP2), 22-29.