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IJISTA
2007
124views more  IJISTA 2007»
15 years 3 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
162
Voted
TCSV
2008
174views more  TCSV 2008»
15 years 3 months ago
A Survey of Vision-Based Trajectory Learning and Analysis for Surveillance
Abstract--This paper presents a survey of trajectory-based activity analysis for visual surveillance. It describes techniques that use trajectory data to define a general set of ac...
Brendan Tran Morris, Mohan M. Trivedi
135
Voted
TSE
2002
133views more  TSE 2002»
15 years 3 months ago
Quality, Productivity, and Learning in Framework-Based Development: An Exploratory Case Study
This paper presents an empirical study in an industrial context on the production of software using a framework. Frameworks are semicomplete applications, usually implemented as a ...
Maurizio Morisio, Daniele Romano, Ioannis Stamelos
152
Voted
REALWSN
2010
15 years 1 months ago
Motes in the Jungle: Lessons Learned from a Short-Term WSN Deployment in the Ecuador Cloud Forest
We study the characteristics of the communication links of a wireless sensor network in a tropical cloud forest in Ecuador, in the context of a wildlife monitoring application. Thi...
Matteo Ceriotti, Matteo Chini, Amy L. Murphy, Gian...
133
Voted
ICIP
2007
IEEE
16 years 5 months ago
MuFeSaC: Learning When to Use Which Feature Detector
Interest point detectors are the starting point in image analysis for depth estimation using epipolar geometry and camera ego-motion estimation. With several detectors defined in ...
Sreenivas R. Sukumar, David L. Page, Hamparsum Boz...