作者: 木質(zhì) 時(shí)間: 2025-3-21 22:58 作者: 不能根除 時(shí)間: 2025-3-22 00:40
Exploring Multilingual Word Embedding Alignments in?BERT Models: A Case Study of?English and?Norwegialysis also shows that embedding a word encodes information about the language to which it belongs. We, therefore, believe that in pre-trained multilingual models’ knowledge from one language can be transferred to another without direct supervision and help solve the data sparsity problem for minor 作者: 親愛 時(shí)間: 2025-3-22 06:05 作者: 大包裹 時(shí)間: 2025-3-22 12:08 作者: Dissonance 時(shí)間: 2025-3-22 16:46 作者: Seizure 時(shí)間: 2025-3-22 20:42 作者: congenial 時(shí)間: 2025-3-22 22:00
Deep Despeckling of?SAR Images to?Improve Change Detection Performancesed method demonstrate superior performance compared to state-of-the-art methods such as DDNet and LANTNet performance. Our method significantly increased the change detection accuracy from a baseline of 86.65% up to 90.79% for DDNet and from 87.16% to 91.1% for LANTNet in the Yellow River dataset.作者: Immunization 時(shí)間: 2025-3-23 05:17
Profiling Power Consumption for?Deep Learning on?Resource Limited Devicesa common approach to facilitate such deployments. This paper investigates the power consumption behaviour of CNN models from the DenseNet, EfficientNet, MobileNet, ResNet, ConvNeXt & RegNet architecture families, processing imagery on board a Nvidia Jetson Orin Nano platform. It was found that energ作者: 鍍金 時(shí)間: 2025-3-23 08:11 作者: Exposition 時(shí)間: 2025-3-23 12:01
Studies in Computational Intelligenceowed by reviewing the current state of XAI before proposing the use of blackboard systems (BBS) to not only share results but also to integrate and to exchange explanations of different XAI models as well, in order to derive an overall explanation for hybrid AI systems.作者: 克制 時(shí)間: 2025-3-23 16:12
Anja Ballis,Tobias Heinz,Mira Schienageldictions, and analyze both baseline and ensemble performance. This research shows that intermediate fine-tuning can create sufficiently performant and diverse inducers for ensembles, and that those ensembles may also outperform single-model baselines on sarcasm detection tasks.作者: PATRI 時(shí)間: 2025-3-23 19:45 作者: inspired 時(shí)間: 2025-3-24 00:04 作者: FACT 時(shí)間: 2025-3-24 06:03
Anja Ballis,Tobias Heinz,Mira Schienagelver, it is crucial to understand the optimal setup for different components of an AL system. This paper presents an evaluation of the effectiveness of different combinations of data representation, model capacity, and query strategy for active learning systems designed for medical image classificati作者: Esalate 時(shí)間: 2025-3-24 09:39 作者: Minatory 時(shí)間: 2025-3-24 13:07
https://doi.org/10.1057/9780230509528how the efficacy of the CT scheme on the ISPRS Potsdam aerial image segmentation dataset. Additionally, we show the generalizability of our scheme by applying it to multiple inherently different transformer architectures. Ultimately, the results show a consistent increase in mean Intersection-over-U作者: 生存環(huán)境 時(shí)間: 2025-3-24 17:10
Christel G?rtner,Heidemarie Winkelsed method demonstrate superior performance compared to state-of-the-art methods such as DDNet and LANTNet performance. Our method significantly increased the change detection accuracy from a baseline of 86.65% up to 90.79% for DDNet and from 87.16% to 91.1% for LANTNet in the Yellow River dataset.作者: Felicitous 時(shí)間: 2025-3-24 21:28
https://doi.org/10.1007/978-3-658-33239-6a common approach to facilitate such deployments. This paper investigates the power consumption behaviour of CNN models from the DenseNet, EfficientNet, MobileNet, ResNet, ConvNeXt & RegNet architecture families, processing imagery on board a Nvidia Jetson Orin Nano platform. It was found that energ作者: 群居男女 時(shí)間: 2025-3-25 01:36 作者: sundowning 時(shí)間: 2025-3-25 05:08 作者: APNEA 時(shí)間: 2025-3-25 08:27 作者: Clinch 時(shí)間: 2025-3-25 15:09
Palgrave Studies in Educational Media pre-trained language models for clinical dialogue error correction. We show that our mask-filling objective specialised for the medical domain?(med-mask-filling) outperforms the best performing commercial ASR system by 10.27%.作者: 戲法 時(shí)間: 2025-3-25 16:36 作者: 不要不誠實(shí) 時(shí)間: 2025-3-25 22:45
Clinical Dialogue Transcription Error Correction with?Self-supervision pre-trained language models for clinical dialogue error correction. We show that our mask-filling objective specialised for the medical domain?(med-mask-filling) outperforms the best performing commercial ASR system by 10.27%.作者: LEVY 時(shí)間: 2025-3-26 03:03
PertCF: A Perturbation-Based Counterfactual Generation Approachture attribution to generate high-quality, stable, and interpretable counterfactuals. We evaluate PertCF on two open datasets and show that it has promising results over state-of-the-art methods regarding various evaluation metrics like stability, proximity, and dissimilarity.作者: intertwine 時(shí)間: 2025-3-26 06:36
0302-9743 ridge, UK,?during?December 12–14, 2023..The 27 full papers and 20 short papers included in this book are carefully reviewed and?selected from 67 submissions. They were organized in topical sections as follows:?Technical Papers:?Speech and Natural Language Analysis,?Image Analysis,?Neural Nets,?Case 作者: 高深莫測 時(shí)間: 2025-3-26 12:14 作者: 禮節(jié) 時(shí)間: 2025-3-26 13:45
Conference proceedings 2023oning and?Short Technical Papers.?Application Papers:?Machine Learning Applications,?Machine Vision Applications,?Knowledge Discovery and Data Mining Applications, other AI Applications and?Short Application Papers..作者: atrophy 時(shí)間: 2025-3-26 20:02
0302-9743 Based Reasoning and?Short Technical Papers.?Application Papers:?Machine Learning Applications,?Machine Vision Applications,?Knowledge Discovery and Data Mining Applications, other AI Applications and?Short Application Papers..978-3-031-47993-9978-3-031-47994-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 外來 時(shí)間: 2025-3-26 22:12
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162158.jpg作者: 急性 時(shí)間: 2025-3-27 03:17 作者: 外科醫(yī)生 時(shí)間: 2025-3-27 07:39 作者: 去才蔑視 時(shí)間: 2025-3-27 11:49
Palgrave Studies in Educational Mediahe reliance on manual note-taking is highly inefficient and leads to transcription errors when digitising notes. Speech-to-text applications designed using Automatic Speech Recognition?(ASR) can potentially overcome these errors using post-ASR error correction. Pre-trained language models are increa作者: FACT 時(shí)間: 2025-3-27 15:28 作者: 吸引力 時(shí)間: 2025-3-27 17:48 作者: liaison 時(shí)間: 2025-3-28 01:16
Anja Ballis,Tobias Heinz,Mira Schienagel the shortage of qualified radiologists, there is an increasing burden on healthcare practitioners, which underscores the need to develop reliable automated methods. Despite the development of novel computational techniques, interpreting medical images remains challenging due to noise and varying ac作者: 為敵 時(shí)間: 2025-3-28 04:29
https://doi.org/10.1057/9780230509528utilizes pre-trained computer vision models to extract high-level image features, has demonstrated remarkable efficacy in identifying images with similar compositions. However, there is a lack of methods for evaluating the embeddings generated by these models, as conventional loss and performance me作者: Epithelium 時(shí)間: 2025-3-28 08:52
https://doi.org/10.1057/9780230509528learning techniques, often used for image classification, to benefit dense downstream prediction tasks such as semantic segmentation. The scheme performs supervised patch-level contrastive learning, selecting the patches based on the ground truth mask, subsequently used for hard-negative and hard-po作者: 腐敗 時(shí)間: 2025-3-28 11:10
Christel G?rtner,Heidemarie Winkelphical region. SAR offers advantages over optical sensors for disaster-related change detection in remote sensing due to its all-weather capability and ability to penetrate clouds and darkness. The performance of change detection methods is affected by several challenges. Deep learning methods, such作者: Sedative 時(shí)間: 2025-3-28 16:33 作者: superfluous 時(shí)間: 2025-3-28 19:46
Christel G?rtner,Heidemarie Winkelt directly observe. The system consists of a virtual problem (in this case a simple game), a simulated user capable of answering natural language questions that can observe and perform actions on the problem, and a Deep Q-Network (DQN)-based chatbot architecture. The chatbot is trained with the goal作者: FAST 時(shí)間: 2025-3-29 02:31 作者: Glucose 時(shí)間: 2025-3-29 06:52
Hansj?rg Schmid,Amir Sheikhzadegans, an instance-based post-hoc explanation method, aim to demonstrate how a model’s prediction can be changed with minimal effort by presenting a hypothetical example. In addition to counterfactual explanation methods, feature attribution techniques such as SHAP (SHapley Additive exPlanations) have a作者: Harrowing 時(shí)間: 2025-3-29 07:54
https://doi.org/10.1007/978-3-031-47994-6artificial intelligence; computer systems; deep learning; machine learning; mathematics; Neural Networks; 作者: HATCH 時(shí)間: 2025-3-29 11:46 作者: 使害羞 時(shí)間: 2025-3-29 17:12 作者: Cryptic 時(shí)間: 2025-3-29 21:14 作者: mediocrity 時(shí)間: 2025-3-30 03:10
Intermediate Task Ensembling for Sarcasm Detectionvelopers use computational methods to parse, process, and understand an ever-increasing volume of natural language text. While recent advances in natural language processing and large language models have improved access to state-of-the-art performance, partly through the evolution of pre-training a作者: 敵意 時(shí)間: 2025-3-30 04:08 作者: Lice692 時(shí)間: 2025-3-30 10:07 作者: 官僚統(tǒng)治 時(shí)間: 2025-3-30 14:03
Confidence Preservation Property in?Knowledge Distillation Abstractionsal network language models for sentiment analysis and content understanding. Some models, like BERT, are complex, and have numerous parameters, which makes them expensive to operate and maintain. To overcome these deficiencies, industry experts employ a knowledge distillation compression technique, 作者: 喚起 時(shí)間: 2025-3-30 17:22
