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Safer Sparse LOD Scanning via Sparse Non-linear Support Vector Regression – This paper explores a deep neural network based detection technique for object detection in 2D object scene sequences. It is a state-of-the-art method by a large margin in all cases. However, learning to make use of existing model-based detection techniques to improve performance is […]

Convolutional neural network – We present a new technique called recurrent neural network (RNN), which is a neural network based neural model for deep architectures. Despite being trained on a relatively small number of examples in a given dataset, RNN has a significant impact on deep learning tasks like image classification. The problem of robust […]

Convolutional Neural Networks, Part I: General Principles – This paper investigates the use of nonlinear networks as basis for modeling decision support systems (PDS). Nonlinear networks are a powerful approach for modeling PDS, as it is simple to describe their model to the user via the network structure and the user behaviour. Unfortunately, these networks […]

An Experimental Evaluation of the Performance of Conditional Random Field Neurons – This paper presents an experimental evaluation of an algorithm called the Random Field Neurons and a model called a Random Field Neuron. The results are very useful and are validated using data from a large clinical trial. We obtain a numerical evaluation of […]

Mapping Images and Video Summaries to Event-Paths – We present an end-of-the-art multi-view, multi-stream video reconstruction pipeline based on Deep Learning. Our deep learning is based on using an encoder-decoder architecture to embed a multi-view convolutional network and feed it to the multi-view convolutional network to reconstruct videos. Since the output of the multi-view convolutional […]

Identify and interpret the significance of differences – We apply the machine learning techniques to solve the largest classification problem of the year on the UCI Computer Vision Challenge, with the goal of predicting object poses in videos captured by a computer user in the video. In this paper, we study the problem of recognizing […]

How Many Words and How Much Word is In a Question and Answers ? – Answer Set Programming has been one of the most developed and influential methods for generating answers. This paper proposes a new method to solve the task of solving a set of logical questions by solving the logical problem. The problem […]

Multi-level object recognition with distributed residual descriptors – This paper deals with a novel object-related neural network (NN) architecture for image-based collaborative filtering. In this design, the network includes the three elements of a discriminative model for each object category and a discriminative model for the image categories, which can generate a generic map which […]

The Power of Zero – We show that, in a variety of domains, the entropy of a function is one of two kinds. The true entropy of a function is, in turn, correlated to the real amount of energy the function has. Our main result is that an exponential function is a function of more […]

Determining the optimal scoring path using evolutionary process predictions – In this paper, we propose a new algorithm for the solution of an approximate Markov Decision Process (MDP) by leveraging the concept of non-monotonic knowledge, which is a property of nonmonotonic systems. We propose a novel method (in the form of the Expectation Maximization Regulator) […]