Background: Ambiguities and anomalies in the Activity of Daily Living (ADL) patterns indicate deviations from Wellness. The monitoring lifestyles could facilitate remote physicians or caregivers to give insight into symptoms disease provide health improvement advice residents; Objective: This research work aims apply lifestyle an ambient assisted living (AAL) system by diagnosing conduct distinguishing variation norm with slightest conceivable fake alert. In pursuing this aim, main objective...

Discriminative representation is essential to keep a unique identifier for each target in Multiple object tracking (MOT). Some recent MOT methods extract features of the bounding box region or center point as identity embeddings. However, when targets are occluded, these coarse-grained global representations become unreliable. To this end, we propose exploring diverse fine-grained representation, which describes appearance comprehensively from and local perspectives. This represen-tation...

Abstract During production and manufacturing, box joint structures with bolt holes are prone to dimensional accuracy errors due systematic failures in devices or inadequate control of welding deformation. In order address the limitations low efficiency high subjectivity associated traditional manual inspection, a inspection technique for structure assisted by point cloud data is proposed. A section size method built that uses normal vector relationship between structural surfaces establish...

The huge domain gap between sketches and photos the highly abstract sketch representations pose challenges for sketch-based image retrieval (\underline{SBIR}). zero-shot (\underline{ZS-SBIR}) is more generic practical but poses an even greater challenge because of additional knowledge seen unseen categories. To simultaneously mitigate both gaps, we propose \textbf{A}pproaching-and-\textbf{C}entralizing \textbf{Net}work (termed "\textbf{ACNet}") to jointly optimize sketch-to-photo synthesis...

The characteristics of collaborative innovation and interactions among core enterprises, users, partners are critical. Research is lacking on how to construct open ecology through institutional design. This study explores enterprises effectively motivate users participate in activities the Internet successfully constructing ecology, using logic theory an exploratory case Xiaomi, a famous Chinese enterprise. findings as follows: (1) three main carried out by ecology—iterative innovation,...

This study explores how Internet enterprises integrate different industries to sustainably develop organizational ecology, using institutional logic theory and an exploratory case of LeEco, a famous Chinese enterprise. The findings are as follows: (1) There two main barriers sustainable development internal ecology: resource information barriers. To overcome these obstacles, managers should carry out series practices so that the ecology obtains both product legitimacy; (2) A new practice,...

Image classification is a challenging problem which aims to identify the category of object in image. In recent years, deep Convolutional Neural Networks (CNNs) have been applied handle this task, and impressive improvement has achieved. However, some research showed output CNNs can be easily altered by adding relatively small perturbations input image, such as modifying few pixels. Recently, Capsule (CapsNets) are proposed, help eliminating limitation. Experiments on MNIST dataset revealed...

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of tumor resection surgery.However, most existing methods are not feasible to be used directly this task due challenge exact edge prediction with some tiny and slender vessels as its clinical criterion.To address problem, we propose a novel deep learning model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA).This model can improve accuracy segments...

Recent research in cross-domain image retrieval has focused on addressing two challenging issues: handling domain variations the data and dealing with lack of sufficient training labels. However, these problems have often been studied separately, limiting practicality significance outcomes. The existing setting is also restricted to cases where labels are known during training, all samples semantic category information or instance correspondences. In this paper, we propose a novel approach...

There are many researches use peer-to-peer model to organize the Grid Information Service (GIS) and have been testified which be able improve scalability reliability of environment. However, Data (DGIS) has its special requirements all approaches P2P used in GIS cannot applied DGIS. In this paper, we propose a new approach for DGIS that imposes deterministic shape based on hypercube topology, allows very efficient query broadcasting. Furthermore, proposed transposition algorithm optimize...

Abstract In order to train an end‐to‐end model for better performance in distinguishing superclasses and make the more sensitive inter‐class differences, authors propose a Feature Context Network (FCNet), novel ensemble framework image retrieval based on clustering (EFC) metric learning. authors' approach, EFC consists of one common feature extractor multiple learning branches. This tree‐like structure not only promotes stability training process but also keeps diversity by using Each branch...

Weakly-supervised temporal action localization task aims to localize boundaries of instances by using only video-level labels. Existing methods primarily adopt Multi-Instance-Learning (MIL) scheme handle this task. The effectiveness MIL depends heavily on the selection top-k snippets, which is unstable and requires manual tuning. To address these deficiencies, we propose an Adaptive Clustering Refining Network (ACRNet). Specifically, present action-aware clustering strategy that adaptable no...

In large-scale, self-organized and distributed systems, such as peer-to-peer (P2P) overlays wireless sensor networks (WSN), a small proportion of nodes are likely to be more critical the system's reliability than others. This paper focuses on detecting cut vertices so that we can either neutralize or protect these nodes. Detection is trivial if global knowledge whole system known but it very challenging when missing. this paper, propose completely scheme where every single node determine...

Images taken under low-light conditions suffer from poor visibility, color distortion, and graininess, all of which degrade the image quality hamper performance downstream vision tasks, such as object detection instance segmentation in field autonomous driving, making enhancement an indispensable basic component high-level visual tasks. Low-light aims to mitigate these issues, has garnered extensive attention research over several decades. The primary challenge arises low signal-to-noise...

Abstract To study the different structure types of flexible packaging material gripping mechanical grippers and their application to working environment, two cylinder-type soft are designed in this paper. According structural characteristics gripper, mathematical analysis is carried out determine coordinate relationship each joint gripper. The plot function MATLAB used plan simulate path curves environment applied respectively; movement gripper analyzed by using fifth-degree polynomial,...

In this paper, the distributed consensus problem is investigated for multiple UAVs systems with nonlinear uncertainty and bounded disturbances under a directed graph. It assumed that aerodynamic characteristics of UAV are uncertainties, output leader time-varying. dynamics model can be divided into two parts, including completely known unknown function. An adaptive neural controller designed backstepping design method. Neural networks used as function approximation technique to compensate...