Training deep neural networks on large datasets containing high-dimensional data requires a amount of computation. A solution to this problem is data-parallel distributed training, where model replicated into several computational nodes that have access different chunks the data. This approach, however, entails high communication rates and latency because computed gradients need be shared among at every iteration. The becomes more pronounced in case there wireless between (i.e., due limited...

Atomistic structures of materials offer valuable insights into their functionality. Determining these remains a fundamental challenge in science, especially for systems with defects. While both experimental and computational methods exist, each has limitations resolving nanoscale structures. Core-level spectroscopies, such as x-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment structure materials. Recently, machine...

In response to the issue that post-training quantization leads performance degradation in mobile deployment, as well problem balanced consideration of deviation by Clipping optimization techniques limits improvement accuracy, this article proposes a novel clipping method named ClipQ, which pays different attention parameters, aiming preferentially reduce important parameters. The weight is positively related its absolute value. Channel information entropy and principal component analysis are...

Compact convolutional neural networks (CNNs) have witnessed exceptional improvements in performance recent years. However, they still fail to provide the same predictive power as CNNs with a large number of parameters. The diverse and even abundant features captured by layers is an important characteristic these successful CNNs. differences this between their compact counterparts rarely been investigated. In CNNs, due limited parameters, are unlikely be obtained, feature diversity becomes...

Effective and efficient retargeting techniques may enrich users' browsing experiences in mobile devices. Existing mesh-based solutions put less efforts making well-tuned meshes. In this paper, we propose a novel adaptive grid based optimization method to retarget an image. First, present entropy measure guide the construction. Then employ quadtree structure adjust granularity adaptively. Furthermore, reduce inappropriate deformation from inconsistent importance assignment, build global model...

Hoaxes are non malicious viruses. They live on deceiving human?s perception by conveying false claims as truth. Throughout history, hoaxes have actually able to influence a lot of people the extent tarnishing victim?s image and credibility. Moreover, wrong misleading information has always been distortion growth. Some were created in way that they can even obtain personal data convincing victims those required for official purposes. different from spams masquerade themselves through address...

Recently, convolutional networks have achieved great successes in the field of computer vision. In order to improve efficiency networks, large amount solutions focusing on training algorithms and parallelism strategies been proposed. this paper, a novel algorithm based look-up table is proposed speed up with small filters by applying GPU. By transforming multiplication operations convolution computation some table-based summation operations, overhead can be reduced largely. The process...

Poor retrieval performance significantly degenerates users' experience of visual search, especially in mobile search. Ideally, users would like to be alerted when bad queries are present, which helps eliminate latency as well waste bandwidth, 3G wireless environment. In this paper, we propose a query prediction (v-QPP) approach predict the effectiveness. We employ latent dirichlet allocation (LDA)to derive topics from image database. From collection statistics, model query's specificity...

Federated learning performs collaborative training of deep models among multiple clients, safeguarding data privacy, security, and legal adherence by preserving locally. While the remains stored in client side, instead being shared with server other recent work has shown that can still be reconstructed local updates or gradients. Different defense techniques have been proposed to address this information leakage from gradient updates, including introducing noise gradients, performing...

Federated learning (FL) performs collaborative training of deep models among multiple clients, safeguarding data privacy, security, and legal adherence by preserving locally. Despite the benefits FL, its wider implementation is hindered communication overheads potential privacy risks. Transiting locally updated model parameters between edge clients servers demands high bandwidth, leading to latency internet infrastructure constraints. Furthermore, recent works have shown that malicious...

With the growth of broadband networks, Vide-on-Demand (VoD) has become realistic. Many significant broadcasting schemes have been proposed to reduce bandwidth requirement for stored popular videos, but they cannot be used support VCR functionality perfectly. Herein, we propose a new scheme, called Segment-Alignment Interactive Broadcasting (SAIB) which can built on top any segment based scheme and supports From our analysis, find that SAIB is suitable smooth fast forward jump playback. A...

High percentage of photovoltaic gain connect to the wire line, so that electricity grid from power distribution receiving end network into a set production, storage, multi-source complex new network, security operation and energy consumption pressure increases. In response above, this paper puts forward distributed ES multi-objective optimization configuration strategy adapted high penetration rate PV. And through county practical example certify approach proposed can effectively mitigate...

Multi-face alignment aims to identify geometry structures of multiple faces in an image, and its performance is essential for the many practical tasks, such as face recognition, tracking, animation. In this work, we present a fast bottom-up multi-face approach, which can simultaneously localize multi-person facial landmarks with high precision. more detail, our architecture maps high-dimensional space all are represented. By clustering features belonging same face, approach align...

Abstract Insulators are important components for achieving electrical insulation and mechanical support, but they prone to various defects in harsh operating environments, which can damage their strength performance. This article proposes the Shuffle YOLOv7 model based on algorithm insulator defect detection, aiming solve weakness of low precision traditional object detection algorithms when facing complex backgrounds small-sized defects. To address issue attention flashover faults...

Recent breakthroughs in text-to-image generation has shown encouraging results via large generative models. Due to the scarcity of 3D assets, it is hardly transfer success that text-to-3D generation. Existing methods usually adopt paradigm DreamFusion, which conducts per-asset optimization by distilling a pretrained diffusion model. The speed ranges from several minutes tens per asset, degrades user experience and also imposes burden service providers due high computational budget. In this...

This paper demonstrates the needs of football websites in Equatorial Guinea (EG) which is one smallest country African continent. The designed with purpose to encourage information sharing and promoting EG team among fans from inside outside EG. research initiated based on three (3) key factors : 1) people would like promote their national team; 2) lack medium share news; 3) need a platform keep themselves updated exchange opinion other fan. Implementing website also could give benefit terms...