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With the growth of crowd phenomena in the real world, crowd scene understanding is becoming an important task in anomaly detection and public security. Visual ambiguities and occlusions, high density, low mobility and scene semantics, however, make this problem a great challenge. In this paper, we propose an end-to-end deep architecture, Convolutional DLSTM (ConvDLSTM), for crowd scene understanding...
Person re-identification is an important task in video surveillance systems. It can be formally defined as establishing the correspondence between images of a person taken from different cameras at different times. In this paper, we present a two stream convolutional neural network where each stream is a Siamese network. This architecture can learn spatial and temporal information separately. We also...
We propose a novel deep learning architecture for regressing disparity from a rectified pair of stereo images. We leverage knowledge of the problem’s geometry to form a cost volume using deep feature representations. We learn to incorporate contextual information using 3-D convolutions over this volume. Disparity values are regressed from the cost volume using a proposed differentiable soft argmin...
Automatic localization of services at the time of logical modeling is a difficult task. This is because of the complexity of models and the scattered nature of enterprise architecture information in organizations, systems as well as actors and applications. However, all information about logical services is described in the eLEL and in the aspects of the business architecture of the Praxeme methodology...
Enabling interfaces to declare (instance) method implementations, Java 8 default methods can be used as a substitute for the ubiquitous skeletal implementation software design pattern. Performing this transformation on legacy software manually, though, may be non-trivial. The refactoring requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling...
The increasing complexity of automotive software systems and the desire for more frequent software and even feature updates require new approaches to the design, integration and testing of these systems. Ideally, those approaches enable an in-field updatability of automotive software systems that provides the same degree of safety guarantees as the traditionally lab-based deployment. In this paper,...
Web service is a popular solution to integrate components when building a software system, or to allow communication between a system and third-party users, providing a flexible and reusable mechanism to access its functionalities. Various web service based systems are prevailing in health service provision. We propose a framework of construction, searching and protection of typed health resources...
Program trace alignment is the process of establishing a correspondence between dynamic instruction instances in executions of two semantically similar but syntactically different programs. In this paper we present what is, to the best of our knowledge, the first method capable of aligning realistically long execution traces of real programs. To maximize generality, our method works entirely on the...
Diverse methods abstracting plant architectures are applied in different FSPMs (Functional Structural Plant Models). The abstracted plant architectural data are not applicable for every FSPM because the data models applied in the diverse methods are not compatible. In this paper, we introduce a logical data exchange model EG (Exchange Graph) for adapting different methods abstracting plant architecture...
Pedestrian detection is an important topic in object detection. Compared with other object detectors, YOLOv2 achieves high accuracy and fast speed for general object detection, however it degrades accuracy when detecting crowed pedestrians. In this paper, combining with the skip structure of FCN, we tailor the YOLOv2 network to improve the accuracy in detecting small pedestrians which appear in groups...
Object-branch coverage (OBC) is often used as a measure of the thoroughness of tests suites, augmenting or substituting source-code based structural criteria such as branch coverage and modified condition/decision coverage (MC/DC). In addition, with the increasing use of third-party components for which source-code access may be unavailable, robust object-code coverage criteria are essential to assess...
The connectivity of industrial automation domain systems has been enhanced by the employment of information and communication technologies. This permits the implementation of systems that are aligned with the vision of the fourth industrial revolution, or Industry 4.0. In this scope, Cyber-Physical Systems (CPS), i.e., integration of cyber and physical systems, enables the control and monitoring of...
Packet forwarding in Software-Defined Networks (SDN) relies on a centralised network controller which enforces network policies expressed as forwarding rules. Rules are deployed as sets of entries into network device tables. With heterogeneous devices, deployment is strongly bounded by the respective table constraints (size, lookup time, etc.) and forwarding pipelines. Hence, minimising the overall...
Human sketches are unique in being able to capture both the spatial topology of a visual object, as well as its subtle appearance details. Fine-grained sketch-based image retrieval (FG-SBIR) importantly leverages on such fine-grained characteristics of sketches to conduct instance-level retrieval of photos. Nevertheless, human sketches are often highly abstract and iconic, resulting in severe misalignments...
In this work, we propose a technique to convert CNN models for semantic segmentation of static images into CNNs for video data. We describe a warping method that can be used to augment existing architectures with very lit- tle extra computational cost. This module is called Net- Warp and we demonstrate its use for a range of network architectures. The main design principle is to use opti- cal flow...
Pixel-level annotations are expensive and timeconsuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recent years have seen great progress in weakly-supervised semantic segmentation, whether from a single image or from videos. However, most existing methods are designed to handle a single background class. In practical applications,...
Recently, CNN-based models have achieved remarkable success in image-based salient object detection (SOD). In these models, a key issue is to find a proper network architecture that best fits for the task of SOD. Toward this end, this paper proposes two-stream fixation-semantic CNNs, whose architecture is inspired by the fact that salient objects in complex images can be unambiguously annotated by...
In multi-class indoor semantic segmentation using RGB-D data, it has been shown that incorporating depth feature into RGB feature is helpful to improve segmentation accuracy. However, previous studies have not fully exploited the potentials of multi-modal feature fusion, e.g., simply concatenating RGB and depth features or averaging RGB and depth score maps. To learn the optimal fusion of multimodal...
In this paper methods and approaches of using ontologies in intelligent tutoring systems are analyzed. Basic model of ontology of course/discipline is defined and its implementation in the AT-TECHNOLOGY workbench is reviewed. Some aspects of using ontological approach for tutoring integrated expert systems construction are discussed.
With the rising trend in research and development of autonomous vehicles, it is important to keep in mind the cost effectiveness of the system. The cost of high-end sensor technologies being astronomically expensive, the research opportunities are restricted to a select few of high-tech companies and research laboratories such as Google, Tesla, Ford, and the likes of it. Hence our main focus is to...
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