In this paper, we explore the application of Recursive Neural Networks on the sentiment analysis task with tweets. Tweets, being a form of communication that has been largely infused with symbols and short-hands, are especially challenging as a sentiment analysis task. In this project, we experiment with different genres of neural net and analyze how models suit the data set in which the nature...

This paper presents a survey of neural network controllers for AUVs. A direct adaptive neural net controller incorporating integral action was designed for the heave motion of the ODIN underwater vehicle. The neural net controller is trained on-line by parallel recursive error prediction method and the critic equation. The influence of the various design parameters of the neural net controller ...

optical coherence tomography (oct) uses the spatial and temporal coherence properties of optical waves backscattered from a tissue sample to form an image. an inherent characteristic of coherent imaging is the presence of speckle noise. in this study we use a new ensemble framework which is a combination of several multi-layer perceptron (mlp) neural networks to denoise oct images. the noise is...

This paper presents the potential of the herein so-called neural net filters in communication systems. The use of integrated signaling and coding techniques in modern modulation schemes has not a right correspondence in the same digital signal processing integrated tools. The neural net filter seems to be the needed contribution. Introduced from de basic neural structure associated with coding ...

This thesis presents new methods in two closely related areas of computer vision: human pose estimation, and gesture recognition in videos. In human pose estimation, we show that random forests can be used to estimate human pose in monocular videos. To this end, we propose a co-segmentation algorithm for segmenting humans out of videos, and an evaluator that predicts whether the estimated poses...

The concatenable processes of a Petri net N can be characterized abstractly as the arrows of a symmetric monoidal category ~(N). However, this is only a partial axiomatization, since it is based on a concrete, ad hoe chosen, category of symmetries Sym N. In this paper we give a completely abstract characterization of the category of concatenable processes of N, thus yielding an axiomatic theory...

Despite the recent success of end-to-end learned representations, hand-crafted optical flow features are still widely used in video analysis tasks. To fill this gap, we propose TVNet, a novel end-to-end trainable neural network, to learn optical-flow-like features from data. TVNet subsumes a specific optical flow solver, the TV-L1 method, and is initialized by unfolding its optimization iterati...

Neural oscillations have been found to occur in the olfactory centers of some vertebrates and invertebrates, including the procerebrum of the terrestrial slug Limax marginatus. Using optical recording with the potential-sensitive dye di-4-ANEPPS, we analyzed the spatiotemporal pattern of procerebral neural activities in response to odorants applied to an in vitro brain-superior tentacle prepara...

This paper introduces TiPo, a new neural net model with superior evolvabilities than all previously known neural net models for dynamic functions. TiPo neural nets can dynamically change their structure with each clock tick. This provides enhanced computability for highly dynamic functions, such as curve following. Our goal is to implement this model in a secondgeneration brain-building machine...