Operational Trans-Resistance Amplifier Based Tunable Wave Active Filter

In this paper, Operational Trans-Resistance Amplifier (OTRA) based wave active filter structures are presented. They are flexible and modular, making them suitable to implement higher order filters. The circuits implement the resistors using matched transistors, operating in linear region, making them well suited for IC fabrication. They are insensitive to parasitic input capacitances and input resistances due to the internally grounded input terminals of OTRA. As an application, a doubly terminated third order Butterworth low pass filter has been implemented, by substituting OTRA based wave equivalents of passive elements. PSPICE simulations are given to verify the theoretical analysis

FoodNet: Recognizing Foods Using Ensemble of Deep Networks

In this work we propose a methodology for an automatic food classification system which recognizes the contents of the meal from the images of the food. We developed a multi-layered deep convolutional neural network (CNN) architecture that takes advantages of the features from other deep networks and improves the efficiency. Numerous classical handcrafted features and approaches are explored, among which CNNs are chosen as the best performing features. Networks are trained and fine-tuned using preprocessed images and the filter outputs are fused to achieve higher accuracy. Experimental results on the largest real-world food recognition database ETH Food-101 and newly contributed Indian food image database demonstrate the effectiveness of the proposed methodology as compared to many other benchmark deep learned CNN frameworks.Comment: 5 pages, 3 figures, 3 tables, IEEE Signal Processing Letter