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Object detection has become an important task for various purposes in our daily lives. Machine learning techniques have been used for this task from earlier but they are used for the classification of image-based species to extract the feature set. This task of deciding the feature set helps to decide the desired object detection. To overcome the object classification problern, this paper proposes a transfer learning-based deep learning method. The different convolutional neural networks (CNN) are studied in this work. Here for the improvement in the result, the majority voting scheme is used. The overall work is carried out on the CUB 200–2011 dataset. The results obtained have shown incredible improvement in the accuracy of the proposed work when compared to the different CNN models.