Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A comprehensive survey on applications of transformers for deep learning tasks
S Islam, H Elmekki, A Elsebai, J Bentahar… - Expert Systems with …, 2024 - Elsevier
Abstract Transformers are Deep Neural Networks (DNN) that utilize a self-attention
mechanism to capture contextual relationships within sequential data. Unlike traditional …
mechanism to capture contextual relationships within sequential data. Unlike traditional …
Text recognition in the wild: A survey
The history of text can be traced back over thousands of years. Rich and precise semantic
information carried by text is important in a wide range of vision-based application …
information carried by text is important in a wide range of vision-based application …
Learning transferable visual models from natural language supervision
State-of-the-art computer vision systems are trained to predict a fixed set of predetermined
object categories. This restricted form of supervision limits their generality and usability since …
object categories. This restricted form of supervision limits their generality and usability since …
Fourier contour embedding for arbitrary-shaped text detection
One of the main challenges for arbitrary-shaped text detection is to design a good text
instance representation that allows networks to learn diverse text geometry variances. Most …
instance representation that allows networks to learn diverse text geometry variances. Most …
Deepsolo: Let transformer decoder with explicit points solo for text spotting
End-to-end text spotting aims to integrate scene text detection and recognition into a unified
framework. Dealing with the relationship between the two sub-tasks plays a pivotal role in …
framework. Dealing with the relationship between the two sub-tasks plays a pivotal role in …
Swintextspotter: Scene text spotting via better synergy between text detection and text recognition
End-to-end scene text spotting has attracted great attention in recent years due to the
success of excavating the intrinsic synergy of the scene text detection and recognition …
success of excavating the intrinsic synergy of the scene text detection and recognition …
Text spotting transformers
In this paper, we present TExt Spotting TRansformers (TESTR), a generic end-to-end text
spotting framework using Transformers for text detection and recognition in the wild. TESTR …
spotting framework using Transformers for text detection and recognition in the wild. TESTR …
Textocr: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text
A crucial component for the scene text based reasoning required for TextVQA and TextCaps
datasets involve detecting and recognizing text present in the images using an optical …
datasets involve detecting and recognizing text present in the images using an optical …
Abcnet v2: Adaptive bezier-curve network for real-time end-to-end text spotting
End-to-end text-spotting, which aims to integrate detection and recognition in a unified
framework, has attracted increasing attention due to its simplicity of the two complimentary …
framework, has attracted increasing attention due to its simplicity of the two complimentary …
Omniparser: A unified framework for text spotting key information extraction and table recognition
Recently visually-situated text parsing (VsTP) has experienced notable advancements
driven by the increasing demand for automated document understanding and the …
driven by the increasing demand for automated document understanding and the …