標(biāo)題: Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi [打印本頁(yè)] 作者: Garfield 時(shí)間: 2025-3-21 16:04
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024影響因子(影響力)
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024影響因子(影響力)學(xué)科排名
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024被引頻次
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024被引頻次學(xué)科排名
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024年度引用
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024年度引用學(xué)科排名
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024讀者反饋
書(shū)目名稱Document Analysis and Recognition - ICDAR 2024讀者反饋學(xué)科排名
作者: 僵硬 時(shí)間: 2025-3-21 23:01
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/284813.jpg作者: MOCK 時(shí)間: 2025-3-22 01:43
https://doi.org/10.1007/978-3-662-13217-3r a source-free DA approach to adapt a given trained model to a new collection—an extremely useful scenario for preserving musical heritage. The method involves re-training the pre-trained model to align the statistics stored from the original data in normalization layers with those of the new colle作者: Ambulatory 時(shí)間: 2025-3-22 06:28 作者: 陰謀小團(tuán)體 時(shí)間: 2025-3-22 09:19
Gerd Lütjering,James C. Williamse only recently been considered in this process. This results in a lack of adequate ground truth datasets needed for the development and benchmarking of OMR systems. In this work, the KuiSCIMA (Jiang Kui Score Images for Musicological Analysis) dataset is introduced. KuiSCIMA is the first machine-re作者: 木質(zhì) 時(shí)間: 2025-3-22 14:05 作者: 木質(zhì) 時(shí)間: 2025-3-22 17:38 作者: disparage 時(shí)間: 2025-3-23 00:35
Bundeszentrale für politische Bildunge of Pretrained Language Models (PLMs) has sparked increased interest in leveraging these models for EQA tasks, yielding promising results. Nonetheless, current approaches frequently neglect the issue of label noise, which arises from incomplete labeling and inconsistent annotations, thereby reducin作者: 高談闊論 時(shí)間: 2025-3-23 01:40 作者: 沒(méi)有貧窮 時(shí)間: 2025-3-23 09:18
Tokolyse beim vorzeitigen Blasensprung?,k of selecting the correct text to use in a comic panel, given its neighbouring panels. Traditional methods based on recurrent neural networks, have struggled with this task due to limited OCR accuracy and inherent model limitations. We introduce a novel Multimodal Large Language Model (Multimodal-L作者: painkillers 時(shí)間: 2025-3-23 13:42 作者: 裂隙 時(shí)間: 2025-3-23 15:40 作者: CORE 時(shí)間: 2025-3-23 19:49
https://doi.org/10.1007/978-3-663-15792-2associated question. Considerable research efforts have been dedicated to addressing this task, leveraging a diversity of semantic matching techniques to estimate the alignment among the answer, passage, and question. However, key challenges arise as not all sentences from the passage contribute to 作者: 終點(diǎn) 時(shí)間: 2025-3-23 23:37
Einleitung Was kommt nach dem Feminismus?,in sensitive or copyrighted information, none of the current DocVQA methods offers strong privacy guarantees..In this work, we explore privacy in the domain of DocVQA for the first time, highlighting privacy issues in state of the art multi-modal LLM models used for DocVQA, and explore possible solu作者: DEMUR 時(shí)間: 2025-3-24 05:08
Il torace: entrarci ed uscirne,al information are efficiently combined. Document Visual Question Answering (Document VQA), due to this multi-modal nature, has garnered significant interest from both the document understanding and natural language processing communities. The state-of-the-art single-page Document VQA methods show i作者: 用手捏 時(shí)間: 2025-3-24 09:22
John F. Brotchie,John W. Dickey,Ron Sharpesting studies have reduced the multi-round dialogue response selection problem to a classification problem. While such approaches have proven effective in retrieval-based dialogue systems, they have not fully exploited the rich contextual understanding of pre-trained models and have been unable to e作者: 具體 時(shí)間: 2025-3-24 11:32 作者: sparse 時(shí)間: 2025-3-24 17:18 作者: bromide 時(shí)間: 2025-3-24 22:22
https://doi.org/10.1007/978-3-031-70552-6Document Analysis Systems; Handwriting Recognition; Scene Text Detection and Recognition; Document Imag作者: exclusice 時(shí)間: 2025-3-25 03:14
978-3-031-70551-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: conservative 時(shí)間: 2025-3-25 06:19 作者: crucial 時(shí)間: 2025-3-25 07:33
Conference proceedings 2024ndwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more...?.作者: 分離 時(shí)間: 2025-3-25 14:52
0302-9743 ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024..The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions..The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recog作者: 珊瑚 時(shí)間: 2025-3-25 18:15
Conference proceedings 20244, held in Athens, Greece, during August 30–September 4, 2024..The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions..The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; ha作者: 止痛藥 時(shí)間: 2025-3-25 21:46
Der Tiefgang der Frage der Topik,xtraction task from VRD is treated as a node classification problem, leveraging graph convolutional networks that process the VRD graphs. We conducted evaluations on five real-world datasets, showcasing notable results and performances that align with established norms.作者: BABY 時(shí)間: 2025-3-26 01:21
0302-9743 ng document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more...?.978-3-031-70551-9978-3-031-70552-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: ORE 時(shí)間: 2025-3-26 06:15 作者: 不幸的人 時(shí)間: 2025-3-26 08:30
Gerd Lütjering,James C. Williams datasets and has proven capable of handling these intricate music structures effectively. The experimental outcomes not only indicate the competence of the model, but also show that it is better than the state-of-the-art methods, thus contributing to advancements in end-to-end OMR transcription.作者: jeopardize 時(shí)間: 2025-3-26 13:07
Gerd Lütjering,James C. Williamst comes with an open-source tool which allows editing, visualizing, and exporting the contents of the dataset files. In total, this contribution promotes the preservation and understanding of cultural heritage through digitization.作者: 的’ 時(shí)間: 2025-3-26 20:40
Source-Free Domain Adaptation for?Optical Music Recognitiong on data from the original training collections (i.e., source-free). Evaluation of diverse music collections in Mensural notation and a synthetic-to-real scenario of common Western modern notation demonstrates consistent improvements over the baseline (no DA), often with remarkable relative improvements.作者: hypotension 時(shí)間: 2025-3-26 22:27 作者: 翻動(dòng) 時(shí)間: 2025-3-27 04:34
The KuiSCIMA Dataset for?Optical Music Recognition of?Ancient Chinese Suzipu Notationt comes with an open-source tool which allows editing, visualizing, and exporting the contents of the dataset files. In total, this contribution promotes the preservation and understanding of cultural heritage through digitization.作者: Bureaucracy 時(shí)間: 2025-3-27 05:51
Tl...Zrieder corpus, containing 1,438 and 1,493 pianoform systems, each with an image from IMSLP and MusicXML ground truth. (c) We train and fine-tune an end-to-end model to serve as a baseline on the dataset and employ the TEDn metric to evaluate the model. We also test our model against the recently publ作者: 返老還童 時(shí)間: 2025-3-27 10:07
Diskussion des Ansatzes von Tobin, proposals through a Tree Proposal Network, which are subsequently refined into hierarchical trees by a Relation Decoder module. To enhance the relation prediction capabilities of UniVIE, we incorporate two novel tree constraints into the Relation Decoder: a Tree Attention Mask and a Tree Level Embe作者: 付出 時(shí)間: 2025-3-27 14:02 作者: 外星人 時(shí)間: 2025-3-27 19:15
mails). DocVQA, for its part, has several types of documents but only 4.5% of them are business documents (i.e. invoice, purchase order, etc.). All of these 4.5% of documents do not meet the diversity of documents that companies may encounter in their daily document flow. In order to extend these li作者: 鬼魂 時(shí)間: 2025-3-28 00:46
Tokolyse beim vorzeitigen Blasensprung?, this dataset, enhancing model input quality and resulting in another 1% improvement. Finally, we extend the task to a generative format, establishing new baselines and expanding the research possibilities in the field of comics analysis. Code is available at ..作者: concubine 時(shí)間: 2025-3-28 02:45 作者: 露天歷史劇 時(shí)間: 2025-3-28 10:11 作者: 墻壁 時(shí)間: 2025-3-28 10:29
https://doi.org/10.1007/978-3-663-15792-2 Conditional Optimal Transport to effectively identify clues by transporting the semantic meaning of one or several words (from the original passage) to selected words (within identified clues), under the prior condition of the question and answer. Empirical studies on several competitive benchmarks作者: Flu表流動(dòng) 時(shí)間: 2025-3-28 15:09
Einleitung Was kommt nach dem Feminismus?,ate that non-private models tend to memorise, a behaviour that can lead to exposing private information. We then evaluate baseline training schemes employing federated learning and differential privacy in this multi-modal scenario, where the sensitive information might be exposed through either or b作者: 無(wú)法治愈 時(shí)間: 2025-3-28 18:51
Il torace: entrarci ed uscirne,r approach utilizes a self-attention scoring mechanism to generate relevance scores for each document page, enabling the retrieval of pertinent pages. This adaptation allows us to extend single-page Document VQA models to multi-page scenarios without constraints on the number of pages during evaluat作者: headlong 時(shí)間: 2025-3-29 00:58
John F. Brotchie,John W. Dickey,Ron Sharpeion method. In the prompt-tuning phase, a pairwise optimization fine-tuning strategy is employed to improve the model’s ability to effectively discriminate between positive and negative samples. In all three datasets, FPPP outperforms the baseline model, resulting in an improvement of the R10@1 metr作者: 陰郁 時(shí)間: 2025-3-29 03:16
,Complementi di topologia generale ?, comprehensiveness of our multimodal summaries. Our proposed methodology attains excellent results, surpassing other text summarization approaches tailored for the specified Indian languages. Furthermore, we enhance the significance of our work by incorporating a user satisfaction evaluation method,作者: semiskilled 時(shí)間: 2025-3-29 07:41
Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng作者: Gerontology 時(shí)間: 2025-3-29 14:05 作者: 光滑 時(shí)間: 2025-3-29 18:25
UniVIE: A Unified Label Space Approach to?Visual Information Extraction from?Form-Like Documents proposals through a Tree Proposal Network, which are subsequently refined into hierarchical trees by a Relation Decoder module. To enhance the relation prediction capabilities of UniVIE, we incorporate two novel tree constraints into the Relation Decoder: a Tree Attention Mask and a Tree Level Embe作者: 斥責(zé) 時(shí)間: 2025-3-29 23:24
Extractive Question Answering with?Contrastive Puzzles and?Reweighted Cluesthe weights of . samples, respectively. The experimental results, conducted on three benchmark datasets, demonstrates the superior performance of the proposed . compared to conventional approaches, highlighting its efficacy in mitigating the label noise and achieving enhanced EQA performance.作者: 實(shí)施生效 時(shí)間: 2025-3-30 01:58
CHIC: Corporate Document for?Visual Question Answeringmails). DocVQA, for its part, has several types of documents but only 4.5% of them are business documents (i.e. invoice, purchase order, etc.). All of these 4.5% of documents do not meet the diversity of documents that companies may encounter in their daily document flow. In order to extend these li作者: ALIEN 時(shí)間: 2025-3-30 04:49 作者: Chromatic 時(shí)間: 2025-3-30 11:23 作者: Maximizer 時(shí)間: 2025-3-30 13:49 作者: 行業(yè) 時(shí)間: 2025-3-30 18:38 作者: periodontitis 時(shí)間: 2025-3-30 23:55
Privacy-Aware Document Visual Question Answeringate that non-private models tend to memorise, a behaviour that can lead to exposing private information. We then evaluate baseline training schemes employing federated learning and differential privacy in this multi-modal scenario, where the sensitive information might be exposed through either or b作者: Cupping 時(shí)間: 2025-3-31 02:28
Multi-page Document Visual Question Answering Using Self-attention Scoring Mechanismr approach utilizes a self-attention scoring mechanism to generate relevance scores for each document page, enabling the retrieval of pertinent pages. This adaptation allows us to extend single-page Document VQA models to multi-page scenarios without constraints on the number of pages during evaluat
