Optimal input sizes for neural network de-interlacing
نویسندگان
چکیده
Interlaced scanning has been used for a long time in analog SDTV systems. With the increasing demand for high resolution video services, a number of countries have started to offer high-definition television broadcasting services. Although recent displays such as LCD and PDP are more suitable for the progressive scan format, the interlaced scan format still constitute a key part of the HDTV standard (e.g., 1920*1080i) and many programs are provided as interlaced signals. Therefore, de-interlacing technique will play an important factor in video quality on flat panel displays.
منابع مشابه
Optimization of Oleuropein Extraction from Olive Leaves using Artificial Neural Network
In this work, the artificial neural networks (ANN) technology was applied to the simulation of oleuropein extraction process. For this technology, a 3-layer network structure is applied, and the operation factors such as amount of flow intensity ratio, temperature, residence time, and pH are used as input variables of the network, whereas the extraction yield is considere...
متن کاملOptimal Rotor Fault Detection in Induction Motor Using Particle-Swarm Optimization Optimized Neural Network
This study examined and presents an effective method for detection of failure of conductor bars in the winding of rotor of induction motor in low load conditions using neural networks of radial-base functions. The proposed method used Hilbert method to obtain the stator current signal push. The frequency and signal amplitude of the push stator were used as the input of the neural network and th...
متن کاملPredicting Force in Single Point Incremental Forming by Using Artificial Neural Network
In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...
متن کاملEstimation of the mean grain size of mechanically induced Hydroxyapatite based bioceramics via artificial neural network
This study focuses on the estimation of the mean grain size of mechanically induced Hydroxyapatite (HA) through the artificial neural network (ANN) model. The mean grain size of HA and HA based nanocomposites at different milling parameters were obtained from previous studies. The data were trained and tested by the neural network modeling. Accordingly, all data (55 sets) were based on the mecha...
متن کاملPrediction and optimization of load and torque in ring rolling process through development of artificial neural network and evolutionary algorithms
Developing artificial neural network (ANN), a model to make a correct prediction of required force and torque in ring rolling process is developed for the first time. Moreover, an optimal state of process for specific range of input parameters is obtained using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. Radii of main roll and mandrel, rotational speed of main roll, pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009