5 papers
Gesture2Music: A Low-Latency Real-Time Framework for Continuous Gesture-Driven Music Generation
Rathinaraja Jeyaraj, Barathi Subramanian, Kapilya Gangadharan +1
Gesture-driven music generation is an emerging human-computer interaction paradigm for touch-free and expressive musical interaction. However, many existing approaches treat the ta…
Contrast-Enhanced Gating in GRUs for Robust Low-Data Sequence Learning
Barathi Subramanian, Rathinaraja Jeyaraj, Anand Paul
Activation functions govern how recurrent networks regulate and transmit information across temporal dependencies. Despite advances in sequence modelling, gated recurrent units (GR…
STARC-9: A Large-scale Dataset for Multi-Class Tissue Classification for CRC Histopathology
Barathi Subramanian, Rathinaraja Jeyaraj, Mitchell Nevin Peterson +5
Multi-class tissue-type classification of colorectal cancer (CRC) histopathologic images is a significant step in the development of downstream machine learning models for diagnosi…
APALU: A Trainable, Adaptive Activation Function for Deep Learning Networks
Barathi Subramanian, Rathinaraja Jeyaraj, Rakhmonov Akhrorjon Akhmadjon Ugli
Activation function is a pivotal component of deep learning, facilitating the extraction of intricate data patterns. While classical activation functions like ReLU and its variants…
From Data to Decisions: The Transformational Power of Machine Learning in Business Recommendations
Kapilya Gangadharan, K. Malathi, Anoop Purandaran +3
This research aims to explore the impact of Machine Learning (ML) on the evolution and efficacy of Recommendation Systems (RS), particularly in the context of their growing signifi…