This paper describes an efficient approach to image annotation. It ranked first on the recent scene categorization track of the ImagEVAL1 benchmark. We show how homogeneous globa...
In recent years, research and development in the field of machine learning and classification techniques have gained paramount importance. The future generation of intelligent e...
— We present here a hardware–friendly version of the Support Vector Machine (SVM), which is useful to implement its feed–forward phase on limited–resources devices such as ...
A major problem in metropolitan areas is searching for parking spaces. In this paper, we propose a novel method for parking space detection. Given input video captured by a camera...
Recognition of mathematical symbols is a challenging task, with a large set with many similar symbols. We present a support vector machine based hybrid recognition system that use...
—The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications ov...
In this paper, we propose a new classification method that addresses classification in multiple categories of textual documents. We call it Matrix Regression (MR) due to its resem...
Iulian Sandu Popa, Karine Zeitouni, Georges Gardar...
—Interactions between transcription factors (TFs) are necessary for deciphering the complex mechanisms of transcription regulation in eukaryotes. In this paper, we proposed a nov...
This paper describes results concerning the robustness and generalization capabilities of kernel methods in detecting coordinated distributed multiple attacks (CDMA) using network...
Srinivas Mukkamala, Krishna Yendrapalli, Ram B. Ba...
In this paper, we report our work on spam filtering with three novel bayesian classification methods: Aggregating One-Dependence Estimators (AODE), Hidden Naïve Bayes (HNB), Loca...