Region proposals are very important for several perfections of remote sensing applications such as vehicle detection, traffic surveillance and intelligent transport system. In this paper, an efficient region proposal approach has been proposed. The framework is organized into two key steps. The first step is based on extracting region proposals using Cascade system. The second step is based on the classification of extracted region proposals which is performed by transfer learning using Convolutional Neural Networks (CNN) and AlexNet architecture is utilized for transfer learning. The aim of this investigation is to evaluate the proposed method for vehicle detection. The selective search (SS) method is also briefly discussed for comparison. The results regarding vehicle detection are very promising.