Evaluation of Basic Convolutional Neural Network, AlexNet and Bag of Features for Indoor Object Recognition

• DOI: 10.18178/ijmlc.2019.9.6.876
• Publication Date: 2019-12-19T06:23:33Z
• Authors: Srie Azrina Zulke...; Fatin Amira Fammy; Zaidah Ibrahim; Nurbaity Sabri
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

This paper evaluates two deep learning techniques that are basic Convolutional Neural Network (CNN) and AlexNet along with a classical local descriptor is Bag of Features (BoF) Speeded-Up Robust Feature (SURF) Support Vector Machine (SVM) classifier for indoor object recognition.A publicly available dataset, MCIndoor20000, has been used in this experiment consists doors, signage, stairs images Marshfield Clinic.Experimental results indicate achieves the highest accuracy followed by CNN BoF.Furthermore, also show BoF, machine technique, can produce high performance as CNN, image recognition.