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In this paper, we present visual analysis techniques to evaluate the performance of HPC task-based applications on hybrid architectures. Our approach is based on composing modern data analysis tools (pjdump, R, ggplot2, plotly), enabling an agile and flexible scripting framework with minor development cost. We validate our proposal by analyzing traces from the full-fledged implementation of the Cholesky...
This paper proposes a place cell model allowing place recognition in the context of robot autonomous navigation. The robustness of this approach lies in the fact that even if one or several patterns characterizing the place are removed or not visible anymore, a place can still be recognized. The recognition process in this work is improved with respect to the state-of-the-art place cells approach...
Modern microprocessors have a number of cores and complicated structures, such as multi-level caches. Behavior analysis of modern complicated processors is important for software performance optimizations, processor architecture researches, and education purposes. Currently, a number of tools are available for checking the behavior of processors such as processor simulators, debuggers and profilers...
The extreme variability in the appearance of a place across the four seasons of the year is one of the most challenging problems in life-long visual topological localization for mobile robotic systems and intelligent vehicles. Traditional solutions to this problem are based on the description of images using hand-crafted features, which have been shown to offer moderate invariance against seasonal...
This paper is an industrial experience report of applying the "Specification by Example" methodology and test-driven development to the development of a core component of a healthcare product. The methods are mapped to the four quadrants of technical debt introduced by Martin Fowler in order to show how they can help to avoid the accumulation of technical debt. The resulting data show that...
In this paper we investigate the image aesthetics classification problem, aka, automatically classifying an image into low or high aesthetic quality, which is quite a challenging problem beyond image recognition. Deep convolutional neural network (DCNN) methods have recently shown promising results for image aesthetics assessment. Currently, a powerful inception module is proposed which shows very...
Repositories of educational resources currently offer various services, including searching and storing learning resources, these services are considered basic in the repositories of educational resources. Universities are producing educational resources, but the reality is that usually these resources generated by students and teachers of the university are often lost. This is mainly because these...
This live demonstration implements an established signal flow platform with its foundation derived from a system of nonlinear integral equations in a MATLAB simulation environment, characterizing the functional behavior of the signal that traverses from the photoreceptor to the ganglion cell in the vision processing architecture. While an increase in computational speed over the conventional method...
This paper proposes a visualization model of any object of moving simple region in order to make the movement of this region and its behavior can be monitored well. This model is developed as an extension of an existing visualization model, which only cope a moving point movement. Simple region is chosen because the need of visualization of its movement is arise. This type of moving region object...
Attention-based bio-inspired vision can be studied as a different way to consider sensor processing, firstly allowing to reduce the amount of data transmitted by connected cameras and secondly advocating a paradigm shift toward neuro-inspired processing for the post-processing of the few regions extracted from the visual field. The computational complexity of the corresponding vision models leads...
Emergency command and control centers (CC) are integrated facilities to assist and handle crisis situations. In these CCs, operators suffer both with information shortage and overload. This paper focuses on the information overload problem. Operators often do not have adequate access to information that may be relevant in the decision-making process. In many CC centers, information is stored without...
Using an experimental approach, this paper proposes a semi-autonomous agent architecture for a remotely operated vehicle (ROV). The system is inspired by Behavior- and Reactive-based architectures using stimulus response blocks to segment behavior. The capability and limitations of the system is demonstrated through a field experiment, where the goal is to approach and localize a structure of interest...
Unmanned airspace access is a key topic to enable unmanned flights in the U.S. National Airspace System. Above the 400-foot AGL limit, unmanned operations need special care and systems to fly safely and reliably. For autonomous flights to be safe, regular parts of daily, economical operations, designs for both the greater airspace and specific avionics must be built on robust systems design principles...
Deep Q-Learning is an effective reinforcement learning method, which has recently obtained human-level performance for a set of Atari 2600 games. Remarkably, the system was trained on the high-dimensional raw visual data. Is Deep Q-Learning equally valid for problems involving a low-dimensional state space? To answer this question, we evaluate the components of Deep Q-Learning (deep architecture,...
We consider the fully automated behavior understanding through visual cues in industrial environments. In contrast to most existing work, which relies on domain knowledge to construct complex handcrafted features from inputs, we exploit a Convolutional Neural Network (CNN), which is a type of deep model and can act directly on the raw inputs, to automate the process of feature construction. Although...
The main purpose of transfer learning is to resolve the problem of different data distribution, generally, when the training samples of source domain are different from the training samples of the target domain. Prediction of salient areas in natural video suffers from the lack of large video benchmarks with human gaze fixations. Different databases only provide dozens up to one or two hundred of...
In this paper, we describe Semantic Bookworm — a tool that supports scholarly text analysis. In contrast to the text-based Bookworm tool, the Semantic Bookworm identifies semantic concepts.
Stereo images have been captured primarily for 3D reconstruction in the past. However, the depth information acquired from stereo can also be used along with saliency to highlight certain objects in a scene. This approach can be used to make still images more interesting to look at, and highlight objects of interest in the scene. We introduce this novel direction in this paper, and discuss the theoretical...
The correct execution of well-defined movements plays a crucial role in physical rehabilitation and sports. While there is an extensive number of well-established approaches for human action recognition, the task of assessing the quality of actions and providing feedback for correcting inaccurate movements has remained an open issue in the literature. We present a learning-based method for efficiently...
Nowaday the mobile cell phone technology growing exponentially and it be a fundamaental element of our modern life style. This technology help users to explore and share their activities through various messaging systems regardless of location and time. Messaging via texting is the essence of mobile communication and connectivity. However, it become increasingly difficult for visually impaired to...
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