In this paper, we propose a model parameter estimation algorithm from block motion vectors for extracting accurate motion information with the assumption that the undergoing motion can be characterized by an affine model. The motion may be caused either by a moving camera or a moving object. The proposed method first extracts motion vectors from a sequence of images by using sizevariable block ...

We show how to use recursive function theory to prove Turing universality of finite analog recurrent neural nets, with a piecewise linear sigmoid function as activation function. We emphasize the modular construction of nets within nets, a relevant issue from the software engineering point of view.

We study two-layer belief networks of binary random variables in which the conditional probabilities Pr[childjparents] depend monotonically on weighted sums of the parents. In large networks where exact probabilistic inference is intractable, we show how to compute upper and lower bounds on many probabilities of interest. In particular, using methods from large deviation theory, we derive rigor...

OBJECTIVES It is unclear if morphology impacts on diastole in hypertrophic cardiomyopathy (HCM). We sought to determine the relationship between various parameters of diastolic function and morphology in a large HCM cohort. SETTING Tertiary referral centre from Stanford, California, USA. PARTECIPANTS 383 patients with HCM and normal systolic function between 1999 and 2011. A group of 100 pr...

Research in distributed AI has dealt with the interactions of agents, both cooperative and self-interested. The Recursive Modeling Method (RMM) is one method used for modeling rational self-interested agents. It assumes that knowledge is nested to a finite depth. An expansion of RMM, using a sigmoid function, was proposed with the hope that the solution concept of the new RMM would approximate ...

Wireless capsule endoscopy (WCE) is a great breakthrough for Gastrointestinal (GI) Tract diagnoses which can view the entire gastrointestinal tract, especially the small bowel, without invasiveness and sedation. However, a tough problem associated with this new device is that too many images to be inspected by naked eyes is difficult for physicians, Thus it is essential to find an automatic and...

In social networks, heterogeneous multimedia data correlate to each other, such as videos and their corresponding tags in YouTube and image-text pairs in Facebook. Nearest neighbor retrieval across multiple modalities on large data sets becomes a hot yet challenging problem. Hashing is expected to be an efficient solution, since it represents data as binary codes. As the bit-wise XOR operations...

A neural network is an information processing system that is widely used in various computer vision applications. This paper discusses an low-latency FPGA-based neural network implementation that does direct computation of the sigmoid activation function.

PRESENTATION OF THE CASE A 61-year-old man undergoes a sigmoid colectomy for a T3N1 (two of 18 nodes) adenocarcinoma of the sigmoid colon. He recovers well and receives 6 months of adjuvant FOLFOX (5-fluorouracil, leucovorin, and oxaliplatin) uneventfully. At his first follow-up visit, the oncologist recommended every 3 month visits for a physical, liver function tests, and carcinoembryonic ant...