Ram D. Sriram

CyberForge: Verified Vulnerability Injection at Repository Level for Cybersecurity Agent Training

Amine Lbath, Manan Suri, Aurélien Delaitre, Vadim Okun et autres

Despite recent advances, frontier large language model (LLM) agents remain limited in discovering and patching complex vulnerabilities in real-world software. Generally available agents can already aid attackers, who only need to find one exploitable weakness, while defenders must continuously identify and patch …

CyberForge: Verified Vulnerability Injection at Repository Level for Cybersecurity Agent Training

Amine Lbath, Manan Suri, Aurélien Delaitre, Vadim Okun et autres

Despite recent advances, frontier large language model (LLM) agents remain limited in discovering and patching complex vulnerabilities in real-world software. Generally available agents can already aid attackers, who only need to find one exploitable weakness, while defenders must continuously identify and patch …

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LineConGraphs : Line Conversation Graphs for Effective Emotion Recognition Using Graph Neural Networks

Craig S. Greenberg, Balaraman Ravindran, Dinesh Manocha, Ram D. Sriram

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Citation Worthiness Assessment using Deep Learning Techniques

R Manjusha, M Logkesh, V A Ashwath, Ram D. Sriram et autres

In the realm of scientific and technological research, the identification of citation worthiness, which involves determining whether a sentence merits citation, is crucial for scholarly integrity and knowledge dissemination. This paper delves into the intricate process of citation worthiness assessment by focusing …

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Federated transfer learning for intrusion detection system in industrial iot 4.0

N.R. Malathy, Shree Harish Kumar G, Ram D. Sriram, Jebocen Immanuel Raj NR

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Machine Learning for Myocardial Infarction complication: A Metrics-Based Investigation of Different Models

Thomas Abraham JV, Ram D. Sriram, V Shashaank

Myocardial infarction, known to be heart attack, is still a major global health concern. Recognizing and categorizing MI complications in a timely manner is crucial for effective patient care and better outcomes. In this study, we present an innovative approach that harness …

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Deep Learning based Bone Fracture Prediction using Convolutional Neural Networks: A Comparative Study of Transfer Learning and Fine-tuning Techniques

Ram D. Sriram, O. Aruna

Computer assisted bone fracture detection system has a vital role in medical automated health-care system. These automation system helps healthcare units to detect the bone fracture accurately. In this proposed paper, the CNN also called as convolutional neural network has been proposed …

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Groundwater Level Prediction: A Novel Study on Machine Learning Based Approach with Regression Models for Sustainable Resource Management

Ram D. Sriram, Jasmeen

Ground water is a natural vital resource with significant implications for sustainable water management. Accurate predictions of groundwater levels is essential for informed decision-making and resource allocation. The paper presents a novel machine learning based approach for groundwater level prediction. Groundwater level …

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An Effective Approach for Reducing Time and Memory Requirements for Sign Language Detection

S S Pravin Sabari Bala, Ram D. Sriram, R. Arun

Sign language serves as a crucial means of communication for individuals who are hard of hearing or deaf, but it is often misunderstood or unrecognized by the hearing population, leading to communication barriers and social exclusion. To address this issue, this research …

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A Comparative Analysis of Interaction Techniques in Virtual Environments

Ram D. Sriram

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An Educational based Intelligent Student Stress Prediction using ML

Somnath Sinha, Ram D. Sriram

Prediction of Stress of a college student is a rare case scenario. Universities generally don’t have a stress predictor as a basic need but, a com-mon counsellors and therapist can be further availed if a student is in stressful state. In this …

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Multimodal Emotion Recognition using Transfer Learning from Speaker Recognition and BERT-based models

Sarala Padi, Seyed Omid Sadjadi, Dinesh Manocha, Ram D. Sriram

Automatic emotion recognition plays a key role in computer-human interaction as it has the potential to enrich the next-generation artificial intelligence with emotional intelligence. It finds applications in customer and/or representative behavior analysis in call centers, gaming, personal assistants, and social robots, …