標(biāo)題: Titlebook: Big Data and Artificial Intelligence; 11th International C Vikram Goyal,Naveen Kumar,Dhruv Kumar Conference proceedings 2023 The Editor(s) [打印本頁] 作者: 游牧 時間: 2025-3-21 17:27
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作者: frugal 時間: 2025-3-21 21:53 作者: 懶鬼才會衰弱 時間: 2025-3-22 04:00 作者: instructive 時間: 2025-3-22 04:55 作者: 責(zé)問 時間: 2025-3-22 09:19 作者: 古老 時間: 2025-3-22 16:34 作者: 彩色的蠟筆 時間: 2025-3-22 17:24 作者: Conclave 時間: 2025-3-22 23:04 作者: promote 時間: 2025-3-23 03:49 作者: Figate 時間: 2025-3-23 06:03 作者: hurricane 時間: 2025-3-23 11:35
IndoorGNN: A Graph Neural Network Based Approach for?Indoor Localization Using WiFi RSSIs navigation, personalization, safety and security, and asset tracking. Some of the commonly used technologies for indoor localization include WiFi, Bluetooth, RFID, and Ultra-wideband. Out of these, WiFi’s Received Signal Strength Indicator (RSSI)-based localization is preferred because WiFi Access作者: 有助于 時間: 2025-3-23 17:19
Ensemble-Based Road Surface Crack Detection: A Comprehensive Approachkers. The timely and efficient detection of road cracks is of utmost importance for maintenance and mitigating further deterioration. Currently, existing techniques to identify cracks entail physical examinations rather than deploying automated image-based techniques, which leads to costly and labor作者: 陰險 時間: 2025-3-23 19:08 作者: 死貓他燒焦 時間: 2025-3-23 22:33 作者: Ossification 時間: 2025-3-24 05:09 作者: 我沒有強(qiáng)迫 時間: 2025-3-24 08:20 作者: Commonwealth 時間: 2025-3-24 12:10 作者: 搏斗 時間: 2025-3-24 18:13
Revolutionizing High School Physics Education: A Novel Datasetues which effectively broaden the dataset’s coverage. The dataset, prioritizing text-based questions, is formatted as JSON objects detailing instructions, inputs, and outputs. Post evaluation, we noted significant scores: . and ., indicating a close alignment between generated and reference texts.作者: archetype 時間: 2025-3-24 19:50 作者: artless 時間: 2025-3-24 23:55
Conference proceedings 2023ed in the following topical sections:??Keynote Lectures,?Artificial Intelligence in Healthcare,?Large Language Models,?Data Analytics for Low Resource Domains,?Artificial Intelligence for Innovative Applications and?Potpourri...?.作者: alleviate 時間: 2025-3-25 04:13 作者: 多產(chǎn)魚 時間: 2025-3-25 08:17 作者: 斷斷續(xù)續(xù) 時間: 2025-3-25 15:09 作者: 母豬 時間: 2025-3-25 17:50 作者: 退出可食用 時間: 2025-3-25 21:55
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/185671.jpg作者: 豐富 時間: 2025-3-26 00:33
Decomposition in Data Mining - A Case Study,TB detection is crucial as it can be dangerous if left untreated. To achieve accurate results, it is essential to have a high-resolution input. This paper introduces a Low and high level feature steering (LHFS) module, which reconstructs high-resolution images by a reference image that contains same作者: ectropion 時間: 2025-3-26 04:46
Data Warehousing, Data Mining, and OLAP,sults in unnecessary, inappropriate, and wasted medical services. In the US, Fraud, Waste, and Abuse (FWA) ranges between $760 billion to $935 billion, accounting for approximately 25% of total healthcare spending. In India, the waste caused by FWA is estimated to be as high as 35%. This is due to a作者: 安撫 時間: 2025-3-26 09:23
Introduction to Data Mining Principles,cument within a source document. In CTG, the generated text draws upon contextual cues from both the source document and the cited paper, ensuring accurate and relevant citation information is provided. Previous work in the field of citation generation is mainly based on the text summarization of do作者: 種族被根除 時間: 2025-3-26 13:02
Studies in Computational Intelligencein accuracy. This paper introduces a comprehensive methodology to construct a resilient dataset focused on High School Physics, leveraging retrieval augmentation. Subsequent finetuning of a Large Language Model through instructional calibration is proposed to elevate outcome precision and depth. The作者: placebo 時間: 2025-3-26 18:37 作者: 煩擾 時間: 2025-3-26 22:25
https://doi.org/10.1007/978-3-540-34351-6 Constructing citations is often time-consuming, requiring researchers to delve into extensive literature and grapple with articulating relevant content. To address this challenge, the field of citation text generation (CTG) has emerged. However, while earlier methods have primarily centered on crea作者: Preamble 時間: 2025-3-27 04:36
Data Mining Trends and Knowledge Discovery,C models possess limitations as they primarily concentrate on single sentences, neglecting the significance of contextual understanding in error correction. While a few models have begun to factor in context alongside target sentences, they frequently depend on inflexible boundaries, which leads to 作者: Bernstein-test 時間: 2025-3-27 07:25 作者: STING 時間: 2025-3-27 13:27 作者: 暗語 時間: 2025-3-27 14:49
,Data Mining: an Introduction – Case Study, model probabilistic dependence between variables. In classical bayesian networks, performing exact as well as approximate inferences are NP-Hard. Quantum circuit developed to represent bayesian network can be used to perform inference, but it is prone to quantum noise and strictly limited by the ma作者: Heresy 時間: 2025-3-27 21:35 作者: gentle 時間: 2025-3-28 00:56
Data Warehousing, Data Mining, and OLAP,kers. The timely and efficient detection of road cracks is of utmost importance for maintenance and mitigating further deterioration. Currently, existing techniques to identify cracks entail physical examinations rather than deploying automated image-based techniques, which leads to costly and labor作者: Metastasis 時間: 2025-3-28 05:56 作者: 大猩猩 時間: 2025-3-28 06:14
https://doi.org/10.1007/978-3-319-50017-1sk such as hate speech detection. In this work, we compare the explainability capabilities of three post-hoc methods on the HateXplain benchmark with different .. Our research is the first work to evaluate the effectiveness of Layerwise Relevance Propagation (LRP) as a post-hoc method for fine-tuned作者: ALT 時間: 2025-3-28 11:09
Big Data and Artificial Intelligence978-3-031-49601-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Clinch 時間: 2025-3-28 17:24 作者: 真繁榮 時間: 2025-3-28 20:06
KG-CTG: Citation Generation Through Knowledge Graph-Guided Large Language Modelsset of standard S2ORC dataset, which only consists of computer science academic research papers in the English Language. Vicuna performs best for this task with 14.15 Meteor, 12.88 Rouge-1, 1.52 Rouge-2, and 10.94 Rouge-L. Also, Alpaca performs best, and improves the performance by 36.98% in Rouge-1作者: invert 時間: 2025-3-28 23:49
SciPhyRAG - Retrieval Augmentation to?Improve LLMs on?Physics Q &Ae and . increase on ROUGE-2 scores. This approach has the potential to be used to reshape Physics Q &A by LLMs and has a lasting impact on their use for Physics education. Furthermore, the data sets released can be a reference point for future research and educational domain tasks such as . and ..作者: explicit 時間: 2025-3-29 04:17 作者: 轎車 時間: 2025-3-29 10:02
GEC-DCL: Grammatical Error Correction Model with?Dynamic Context Learning for?Paragraphs and Scholar we substantiate the efficacy of our approach, achieving substantial F. score enhancements: 77% increase, 19.61% boost, and 10.49% rise respectively, compared to state-of-the-art models. Furthermore, we contrast our model’s performance with LLaMA’s GEC capabilities. We extend our investigation to sc作者: Parallel 時間: 2025-3-29 12:02
A Deep Learning Emotion Classification Framework for?Low Resource Languageslassification model is selected through experimentation that compares machine learning models and pre-trained models. Machine learning and deep learning models are SVM, Logistic Regression, Random Forest, CNN, BiLSTM, and CNN+BiLSTM. The pre-trained models, mBERT, IndicBERT, and a hybrid model, mBER作者: 使乳化 時間: 2025-3-29 17:32 作者: 緩解 時間: 2025-3-29 21:31 作者: 泄露 時間: 2025-3-30 01:30 作者: aviator 時間: 2025-3-30 04:32 作者: onlooker 時間: 2025-3-30 08:47 作者: Exterior 時間: 2025-3-30 14:34
Explaining Finetuned Transformers on?Hate Speech Predictions Using Layerwise Relevance Propagationnd to concentrate the text information in the embeddings corresponding to early tokens of the text. Therefore, our findings demonstrate that LRP relevance values at the input of fine-tuning layers are not a good representative of the rationales behind the predicted score.作者: arthroscopy 時間: 2025-3-30 17:05 作者: 拋棄的貨物 時間: 2025-3-30 21:25
Introduction to Data Mining Principles,set of standard S2ORC dataset, which only consists of computer science academic research papers in the English Language. Vicuna performs best for this task with 14.15 Meteor, 12.88 Rouge-1, 1.52 Rouge-2, and 10.94 Rouge-L. Also, Alpaca performs best, and improves the performance by 36.98% in Rouge-1作者: CHART 時間: 2025-3-31 01:26 作者: 腐敗 時間: 2025-3-31 07:22
