Prasanth Lade

picture of CUbiC member

Prasanth Lade

Position

Ph.D. Student Researcher

Department

CUbiC

Contact

prasanthl@asu.edu

Publications

Coupled Support Vector Machines for Supervised Domain Adaptation
Venkateswara H, Lade P, Ye J, Panchanathan S,
2015
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection
Venkateswara H, Lade P, Lin B, Ye J, Panchanathan S,
2015
Semantic Feature Projection for Continuous Emotion Analysis
P. Lade, T. McDaniel, S. Panchanathan,
2014
Detection of changes in human affect dimensions using an adaptive temporal topic model
P. Lade, V. Balasubramanian, S. Panchanathan, H. Venkateswara,
2013
Multiresolution Match Kernels for Gesture Video Classification
H. Venkateswara, V. Balasubramanian, P. Lade, S. Panchanathan,
2013

Projects

Effective communication requires a shared context. In face-to-face interactions, parts of this shared context are the number and location of people, their facial expression, head pose, eye contact, and movements of each person engaged in a conversation. Faces serve an…

Traditional approaches to human activity recognition relying on vision as the primary sensory medium have met with little success. The emergence of the ubiquitous and pervasive paradigm of computing has ushered in new low bandwidth wearable, unobtrusive, inexpensive and…

Smart Homes are equipped with several sensors and one set of useful sensors are activation sensors that give out On/Off information as and when a resident passes by. The frequency with which these sensors may get fired depends on the activity of the smart home resident.…

Individuals with cognitive, developmental and learning disabilities – in particular, Autism Spectrum Disorders (ASD) - have a significant social communication impairment, a situation that can often lead to social isolation. Reducing the need for formal care services for…