Top Research Papers on OCR

The TrOCR model is simple but effective, and can be pre-trained with large-scale synthetic data and fine-tuned with human-labeled datasets, and outperforms the current state-of-the-art models on the printed, handwritten and scene text recognition tasks.

Analysis SVM for OCR system performance that is providing a good result that is configured with machine learning approach has proved Statistical SVM for OCR system performance that is providing a good result that is configured with machine learning approach.

This paper proposes a practical ultra lightweight OCR system, i.e., PP-OCR, with an overall model size of only 3.5M, and introduces a bag of strategies to either enhance the model ability or reduce the model size.

TextScanner bears three characteristics: it belongs to the semantic segmentation family, as it generates pixel-wise, multi-channel segmentation maps for character class, position and order, and also adopts RNN for context modeling.

This study presents a deep ALPR system designed to be applicable to multinational LPs, mainly based on the you only look once (YOLO) networks, and proposes a layout detection algorithm that can extract the correct sequence of LP numbers from multinational LLP.

A deep learning (DL) system with two convolutional neural network (CNN) architectures (named HMB1 and HMB2); with the appliance of optimization, regularization, and dropout techniques is introduced to serve as a baseline for future research on handwritten Arabic text.

The importance of enhancing quality of OCR results by studying their effects on information retrieval and natural language processing applications is clarified by defining the post-OCR processing problem, illustrating its typical pipeline, and reviewing the state-of-the-art post- OCR processing approaches.

A series of extrinsic assessment tasks are performed using popular, out-of-the-box tools in order to quantify the impact of OCR quality on these tasks, finding a consistent impact resulting from OCR errors on downstream tasks with some tasks more irredeemably harmed by O CR errors.

An intrusion pattern recognition scheme based on Gramian Angular Field (GAF) and convolutional neural network (CNN) for the dual Mach–Zehnder Interference (DMZI) distributed fiber perimeter security system, which has the advantages of fast recognition speed and high recognition accuracy rate.

This review enumerates various important considerations for designing and interpreting cellular and mitochondrial bioenergetics experiments, some common challenges and pitfalls in data interpretation, and some potential “next steps” to be taken that can address these highlighted challenges.

The Potato crop (Solanum tuberosum L.) is one of the most important vegetable food crop grown globally. The yield of potato crop is greatly hampered both in quality and quantity by fungal blight diseases which pose a major threat to the global food security. Late blight caused by Phytophthora infestans and early blight caused by Alternaria solani are the most devastating foliage diseases for potato crops. In reality, the farmers presume such disorders by visualizing mainly the color change in the potato leaves that is usually risky due to subjectivity and huge time consumption. Under such situ...

It is reported that T7 bacteriophage Ocr, a DNA mimic protein that protects the phage from the defensive action of type I restriction–modification systems, is also active against BREX.

A neuro-inspired optical sensor array based on two-dimensional NbS2/MoS2 hybrid films featured remarkable photo-induced conductance plasticity and low electrical energy consumption and was experimentally implemented such that the post-processing could yield a high restoration accuracy.

When it was originally published in a two-volume edition in 1935, Ralph Barton Perry's magisterial work on William James was greeted with much critical acclaim. A briefer one-volume edition was published in 1947 to serve as both a systematic account of James's development and a repository of selections from his unpublished writings. The one-volume work (which forms the basis for this new paperback edition) offers a brief and convenient sourcebook of James's thought, set forth in terms that require no previous familiarity with technical problems of philosophy and psychology. An anthology of wel...

A character network is a graph extracted from a narrative, in which vertices represent characters and edges correspond to interactions between them. A number of narrative-related problems can be addressed automatically through the analysis of character networks, such as summarization, classification, or role detection. Character networks are particularly relevant when considering works of fictions (e.g. novels, plays, movies, TV series), as their exploitation allows developing information retrieval and recommendation systems. However, works of fiction possess specific properties making these t...

This work uses deep reinforcement learning to learn controllers that achieve goal-directed movements in data-driven generative models of human movement using autoregressive conditional variational autoencoders, or Motion VAEs.

We propose a deep videorealistic 3D human character model displaying highly realistic shape, motion, and dynamic appearance learned in a new weakly supervised way from multi-view imagery. In contrast to previous work, our controllable 3D character displays dynamics, e.g., the swing of the skirt, dependent on skeletal body motion in an efficient data-driven way, without requiring complex physics simulation. Our character model also features a learned dynamic texture model that accounts for photo-realistic motion-dependent appearance details, as well as view-dependent lighting effects. During tr...

The experimental results show that the algorithm proposed in this paper can effectively recognize face masks and realize the effective monitoring of personnel, and YOLOV5, the most powerful objection detection algorithm at present, is effective in the actual environment.

This literature survey gives a concise introduction to ASR and provides an overview of the general architectures dealing with speaker recognition technologies, and upholds the past, present, and future research trends in this area.

With their distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person's identity. This fully updated third edition provides in-depth coverage of the state-of-the-art in fingerprint recognition readers, feature extraction, and matching algorithms and applications. Deep learning (resurgence beginning around 2012) has been a game changer for artificial intelligence and, in particular, computer vision and biometrics. Performance improvements (both recognition accuracy and speed) for most biome...

This tutorial review describes work on synthetic receptors which bind carbohydrates through non-covalent interactions, mimicking the strategies used in biology, and augurs well for real-world applications.

Abstract Analyses of seismic data from the InSight mission have provided the first in situ constraints on the thickness of the crust of Mars. These crustal thickness constraints are currently limited to beneath the lander that is located in the northern lowlands, and we use gravity and topography data to construct global crustal thickness models that satisfy the seismic data. These models consider a range of possible mantle and core density profiles, a range of crustal densities, a low‐density surface layer, and the possibility that the crustal density of the northern lowlands is greater than ...

This literature review attempts to present an entire picture of the field of scene text recognition, which provides a comprehensive reference for people entering this field and could be helpful in inspiring future research.

We conducted an integrative data analysis to examine the hedonic character of nostalgia. We combined positive and negative affect measures from 41 experiments manipulating nostalgia ( N = 4,659). Overall, nostalgia inductions increased positive and ambivalent affect, but did not significantly alter negative affect. The magnitude of nostalgia’s effects varied markedly across different experimental inductions of the emotion. The hedonic character of nostalgia, then, depends on how the emotion is elicited and the benchmark (i.e., control condition) to which it is compared. We discuss implications...

The values of nationalism can be learned from educational materials that are oriented towards character development. Character education is part of a revolutionary zone among students, therefore character education is a very important part to be urgently developed in the minds of the student head because students are the next generation who will lead the nation and state. Character learning that is oriented towards the values of nationalism can overcome various social problems. Building character for the current generation is one of the goals of national education. The Ministry of National Edu...

By visualizing features before and after DCCA transformation on the SEED-V data set, it is found that the transformed features are more homogeneous and discriminative across emotions.

It is suggested that selected humoral fluid-phase PRMs can play an important role in resistance to, and pathogenesis of, COVID-19, a finding with translational implications.

Face recognition has become the future development direction and has many potential application prospects and is introduced in the general evaluation standards and the general databases of face recognition.

This work presents Multiview Transformers for Video Recognition (MTV), a model that consists of separate encoders to represent different views of the input video with lateral connections to fuse information across views and achieves state-of-the-art results on six standard datasets.

State-of-the-art integrated optical memory technologies and optical RAM cell demonstrations describing the physical mechanisms of several key devices along with their performance metrics in terms of their energy, speed and footprint are reviewed.

The knowledge and algorithms involved in each part are introduced with detailed analysis, including some commonly used datasets, emotion models, feature extraction, and emotion recognition algorithms.

This review discusses state-of-the-art developments, as well as emerging trends, in computational metastructures as disruptive platforms for spatial optical analog computation and discusses two fundamental approaches based on general concepts of spatial Fourier transformation and Green’s function.

This study explores different feature extraction methods, state-of-the-art classification models, and vis-a-vis their impact on an ASR.

The hypotheses behind their existence, the methods used to construct or protect against them, and the capacity to transfer adversarial examples between different machine learning models are introduced.

Mesoscale convective systems (MCSs) describe organized groupings of thunderstorms in the tropics and mid-latitudes that span thousands of square kilometres. While recognized for over a century, the advent of satellite and radar observations, as well as atmospheric-model simulations, has brought about their increased understanding. In this Review, we synthesize current knowledge on MCS formation, climatological characteristics, hazardous weather, predictive capacity and projected changes with anthropogenic warming. Driven by typical deep moist convective processes (moisture, lift and instabilit...

The main aim of the research work is to discuss the various methods and techniques used till now by different research scholars for iris recognition and various steps required in iris Recognition process.

Experimental results show that the identification accuracy of the proposed ANPR exceeds 95%, demonstrating its potential in practical applications and suggestions for future research to improve stability and efficiency.

The background of pedestrian attribute recognition (PAR), including the fundamental concepts of pedestrian attributes and corresponding challenges are introduced, and existing benchmarks, including popular datasets and evaluation criterion are introduced.

This paper proposes a review of research on face recogni­tion techniques, algorithms and existing applications, with their advantages and disadvantages, and presents fu­ture directions of development in the field of face recognition.

The design of Kaldi is described, a free, open-source toolkit for speech recognition research that provides a speech recognition system based on finite-state automata together with detailed documentation and a comprehensive set of scripts for building complete recognition systems.