Autoregressive Sequence-To-Sequence (Seq2Seq) models are the foundation of many Deep Learning achievements in major research fields such as Vision and Natural Language Processing. However, their limitations motivated researchers to explore different architectures methodologies toward bidirectional solutions. In this work, we introduce Bidirectional Awareness Induction (BAI), a flexible training method that enhances information retained subset network results, which call pivot, through loss...

We introduce a method called the Expansion mechanism that processes input unconstrained by number of elements in sequence. By doing so, model can learn more effectively compared to traditional attention-based approaches. To support this claim, we design novel architecture ExpansionNet v2 achieved strong results on MS COCO 2014 Image Captioning challenge and State Art its respective category, with score 143.7 CIDErD offline test split, 140.8 online evaluation server 72.9 AllCIDEr nocaps...

We introduce a method called the Expansion mechanism that processes input unconstrained by number of elements in sequence. By doing so, model can learn more effectively compared to traditional attention-based approaches. To support this claim, we design novel architecture ExpansionNet v2 achieved strong results on MS COCO 2014 Image Captioning challenge and State Art its respective category, with score 143.7 CIDErD offline test split, 140.8 online evaluation server 72.9 AllCIDEr nocaps...

Abstract Modern teaching has made significant progress, with many advanced equipment and technologies being introduced into the process. Experimental of engineering design courses is important. Due to limited resources, students need effective guidance during laboratory time. We will introduce artificial intelligence solutions education. use technology for classroom behavior analysis improve practice courses' effectiveness. In an instructional milieu, image acquisition tools such as cameras...

Most recent state of the art architectures rely on combinations and variations three approaches: convolutional, recurrent self-attentive methods. Our work attempts in laying basis for a new research direction sequence modeling based upon idea modifying length. In order to do that, we propose method called "Expansion Mechanism" which transforms either dynamically or statically input into one featuring different Furthermore, introduce novel architecture that exploits such achieves competitive...

Summary In unmanned aerial vehicles navigation, path planning is aimed at obtaining the optimal safety between start and destination locations. The efficiency optimality criterion depend on environment method adopted. this paper, a general fast framework proposed for navigation. Standard A* search performed online roadmap, which consists of segments that are pre‐computed offline with aid multi‐resolution grid terminate somewhere along boundary adjacent cells. Fast marching (FMM) was employed...

Abstract Digital Breast Tomosynthesis (DBT) is a modern 3D Computed Tomography X-ray technique for the early detection of breast tumors, which receiving growing interest in medical and scientific community. Since DBT performs incomplete sampling data, image reconstruction approaches based on iterative methods are preferable to classical analytic techniques, such as Filtered Back Projection algorithm, providing fewer artifacts. In this work, we consider Model-Based Iterative Reconstruction...

The emergence of digital music platforms has fundamentally transformed the way we engage with and organize music. As playlist creation gained widespread popularity, there is an increasing desire among aficionados industry experts to comprehend factors that drive success. This paper presents a machine learning-based approach designed predict success playlists. By analyzing various musical characteristics songs, our model achieves impressive accuracy 89.6% in predicting Notably, it exhibits...

Autoregressive Sequence-To-Sequence models are the foundation of many Deep Learning achievements in major research fields such as Vision and Natural Language Processing. Despite that, they still present significant limitations. For instance, when errors occur early steps prediction, whole output is severely affected. Such reliance on previously predicted tokens inherent computational unfriendliness sequential algorithms, motivated researchers to explore different architectures methods search...

Image Captioning is an important Language and Vision task that finds application in a variety of contexts, ranging from healthcare to autonomous vehicles. As many real-world applications rely on devices with limited resources, much effort the field was put into development lighter faster models. However, current optimizations focus Transformer architecture contrast existence more efficient methods. In this work, we introduce SwiFTeR, almost entirely based Fourier Transform Retention, tackle...

The deployment of Pre-trained Language Models in memory-limited devices is hindered by their massive number parameters, which motivated the interest developing smaller architectures. Established works model compression literature showcased that small models often present a noticeable performance degradation and need to be paired with transfer learning methods, such as Knowledge Distillation. In this work, we propose parameter-sharing method consists sharing parameters between embeddings...

Reinforcement Learning (RL) offers a promising solution to enable evolutionary automated driving. However, the conventional RL method is always concerned with risk performance. The updated policy may not obtain performance enhancement, even leading deterioration. To address this challenge, research proposes High Confidence Policy Improvement Learning-based (HCPI-RL) planner. It intended achieve monotonic evolution of A novel update paradigm designed newly learned consistently surpass that...

Error diffusion dithering is a technique that used to represent grey-scale image in format usable by printer. At every step, an algorithm converts the value of pixel new within allowed ones, generating conversion error. To achieve effect continuous-tone illusion, error distributed neighboring pixels. Among existent algorithms, most commonly Floyd-Steinberg. However, this suffers two issues: artifacts and slowness. Regarding artifacts, those are textures can appear after elaboration, making...

Dithering or error diffusion is a technique used to obtain binary image, suitable for printing, from grayscale one.At each step, the algorithm computes an allowed value of pixel one, applying threshold and, therefore, causing conversion error.To optical illusion continuous tone, obtained distributed adjacent pixels.In literature there are many algorithms this type, cite some Jarvis, Judice and Ninke (JJN), Stucki, Atkinson, Burkes, Sierra but most known Floyd-Steinberg.We compared various...

Diaphragm gas meter is a specialized flow that measures the volume of fuel such as natural and coal gas. Valve bonnet valve seat are key parts diaphragm meter, which compose main factors its metering error. The widely detecting ways direct observational method pneumatic pressure method. Direct only realizes qualitative detection with lacking science. Pneumatic can realize quantitative detection, but low accuracy bad reliability. In order to evaluate tightness accurately, surface texture was...

White light interference technique for topography measurement effectively avoids phase ambiguity in phase-shifting interferometry. The spatial frequency domain algorithm based on scanning white has the advantage of insensitivity to noise and higher calculation accuracy compared with other methods. sensor is constructed nano positioning measuring machine (NMM), calibrated step height standard 100±3nm measured. adopted data processing, repetitive test result 97.9nm deviation 0.48nm are...

This special issue of Concurrency and Computation: Practice Experience provides a forum for presenting advances current research development in all aspects Parallel Distributed Computing Communications.Because the tremendous broad spectrum technologies topics including wireless networking, cloud computing sensor systems, distributed communications has evolved into an active important area development.The past decade witnessed proliferation powerful parallel systems practice high performance...

SPC technology was applied to the process of DVR production a company in Hangzhou Zhejiang province China. The product defects were analyzed statistically first. main effects which affects performance found by T-type matrix chart analysis.

The Image Captioning research field is currently compromised by the lack of transparency and awareness over End-of-Sequence token (<Eos>) in Self-Critical Sequence Training. If <Eos> omitted, a model can boost its performance up to +4.1 CIDEr-D using trivial sentence fragments. While this phenomenon poses an obstacle fair evaluation comparison established works, people involved new projects are given arduous choice between lower scores unsatisfactory descriptions due competitive nature...