• STUDENT-CENTERED AUTOMATED FEEDBACK USING TRANSFORMER BASED APPROACH 

  William, Tom Jacob; Sumod, Sundar (2024-06-30)

  Effective communication between teachers and students is essential in today’s educational environment. This project presents a transformer model that has been designed for the ed- ucational environment. With the use of ...
• DEEP LEARNING BASED ARRHYTHMIA DISEASE DETECTION USING ELECTROCARDIOGRAM SIGNALS 

  Shanimol, Shajan; Christy, D Ponnan (2024-06-30)

  The primary objective of this work is to use the patient’s electrocardiogram (ECG) to develop a method for early diagnosis of Arrhythmia disease. Traditional methods of diagnosing Ar- rhythmia often require extensive ...
• PATH PLANNING IN ROBOTICS USING HYBRID Q-LEARNING APPROACH 

  Sachin, John Thomas; Imthias, Ahamed T P (2024-06-30)

  Reinforcement learning is a technique that enables agents to learn optimal behaviors through interactions with their environment, using rewards and penalties to shape their actions. In this project, we address the challenge ...
• Financial and Investment Management System using Transformers 

  Reniya, Shajahan; Fousia M, Shamsudeen (2024-06-30)

  In the contemporary landscape of stock market analysis, the utilization of advanced nat- ural language processing techniques has become increasingly prevalent. This work presents the application of the Phi 2 Transformer ...
• NEURAL STYLE TRANSFER WITH VGG19 FOR ENHANCED IMAGE GENERATION 

  Munees, N; Sumod, Sundar (2024-06-30)

  This work investigates the use of Neural Style Transfer (NST) with the VGG19 network to achieve artistic manipulation of natural images. NST offers a powerful technique to create new images by combining the content of a ...
• INVESTIGATING THE EFFICIENCY OF ALZHEIMERS DISEASE CLASSIFICATION BY RADIOMIC FEATURES & DEEP LEARNING TECHNIQUES 

  Muhammed, Sufail M K; Nissan, Kunju (2024-06-30)

  Alzheimer’s Disease (AD) poses a significant global health challenge, underscoring the need for advanced tools facilitating early and precise diagnosis. Previous studies have em- ployed various traditional machine learning ...
• Automatic recognition of epileptic seizure using long term EEG 

  Muhammed, Ajmal N; Mubarak, Ali M (2024-06-30)

  Epileptic seizures occur due to disorder in brain functionality which can affect patient’s health. Prediction of epileptic seizures before the beginning of the onset is quite useful for pre- venting the seizure by ...
• RESTORING OF 2D SURGERY SCENES IMAGES THROUGH INPAINTING USING GAN 

  Mithun, M; Chinnu, Jacob (2024-06-30)

  In recent years, surgical techniques have significantly advanced with the adoption of mini- mally invasive procedures that prioritize precision and reduced patient recovery time. How- ever, limited visibility remains a ...
• DEVELOPING A CLASSIFICATION MODEL AND SEMANTIC SIMILARITY DETECTION OF SYSTEM AND SOFTWARE REQUIREMENTS USING SENTENCE TRANSFORMERS 

  V R Manasi, Manasan; Adarsh, S (2024-06-28)

  Reading and understanding similar type of requirements using human interventions can be a laborious and time-consuming task. However, the complexity of natural language makes it difficult to accurately identify semantic ...
• TEXT-DRIVEN HUMAN MOTION SYNTHESIS USING DIFFUSION MODELS 

  K J, Ananthakrishnan; Sumod, Sundar (2024-06-28)

  The term ”text-to-motion generation” pertains to the procedure of producing sequences of human motion by using textual input. The work at hand presents considerable challenges, mostly stemming from the wide range of ...
• ESTABLISHING CONSENSUS IN MULTI-AGENT SYSTEMS VIA REINFORCEMENT LEARNING TECHNIQUE 

  Irfan, E; Resmi, R (2024-06-28)

  A multi agent system(MAS) in the context of artificial intelligence refers to a system composed of multiple interacting agents, which can be entities or robots. These agents work together or compete to achieve individual ...
• ANALYSING EEG SIGNAL TO RECOGNISE EMOTIONS 

  Dilish, Jose; Mubarak, Ali M (2024-06-28)

  Emotion recognition through Electroencephalography (EEG) is widely acknowledged as a reliable method with diverse applications including defense, aerospace, and medical do- mains. This research aims to detect emotions ...
• NAMED ENTITY EXTRACTION IN STRUCTURED FORMAT FROM RESUME USING LLAMA 2 

  Ann B, Merin; Anzar, S M (2024-06-28)

  Recruitment agencies and firms encounter a significant challenge in handling the mul- titude of resumes they receive daily, which come in various formats such as PDFs, DOCX files, and with diverse layouts. Extracting ...
• 3D ATTENTION U-NET BASED MODEL FOR MULTI-REGION BRAIN TUMOR SEGMENTATION 

  ANILA, KUNJUMON; Chinnu, Jacob (2024-06-28)

  Brain tumors are characterized by the abnormal growth of cells within or near the brain tissues. Accurate segmentation of brain tumors is crucial for effective clinical decision mak- ing. The traditional models encounter ...
• HAND GESTURE CLASSIFICATION USING SEMG SIGNALS 

  ABHIN, SHANKAR KURUP C. M.; Sumod, Sundar (2024-06-30)

  This work presents the development of a robust hand gesture classification system based on surface Electromyography (SEMG) signals, designed for real-world applications. The project utilized data collected from subjects ...
• CAN INTRUSION DETECTION SYSTEM USING GAN 

  Sreelakshmi, S Baiju; Adarsh, S (2023-05)

  Throughout the history of automobiles, advancements have been made to improve the safety and comfort of driving. One of the latest developments involves replacing the wiring between electronic control units (ECUs) with ...
• DRIVER MANEUVER PREDICTION VIA FEATURE FUSION USING DEEP LEARNING 

  Sarath, Mohan; Adarsh, S (2023-05)

  The eighth most common cause of death and the top cause of death for people aged 5-29 are traffic accidents. Automated vehicles and driver-assistance systems have emerged as a promising alternative to lower the number ...
• INTELLIGENT POTHOLE DETECTION AND ASSESSMENT SYSTEM: AREA AND DEPTH ESTIMATION 

  Rufus Rubin, Oscar Fernandez; Chinnu, Jacob (2023-05)

  Economic and social prosperity relies heavily on well-developed and maintained highways, but lack of funding and resources makes highway maintenance difficult. Potholes and early road deterioration pose significant risks ...
• WAVELET BASED CNN FOR DIAGNOSIS OF LUNG DISEASES USING CHEST X-RAYS 

  Jumana, R; Chinnu, Jacob (2023-07)

  Lung diseases are widespread worldwide, including conditions such as lung nodules, pneu monia, asthma, tuberculosis, fibrosis, etc. It is crucial to diagnose lung disease promptly. In this study, wavelet-based Convolutional ...
• APPRAISAL-GUIDED PROXIMAL POLICY OPTIMIZATION: MODELING PSYCHOLOGICAL DISORDERS IN DYNAMIC GRID WORLD 

  Hari, Prasad; Chinnu, Jacob (2023-07)

  The increasing integration of artificial intelligence (AI) across multiple domains has high lighted the significance of comprehending and replicating human-like cognitive processes in AI. The incorporation of emotional ...

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