標(biāo)題: Titlebook: ; [打印本頁] 作者: mountebank 時(shí)間: 2025-3-21 19:08
書目名稱Generalizing from Limited Resources in the Open World影響因子(影響力)
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書目名稱Generalizing from Limited Resources in the Open World被引頻次學(xué)科排名
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書目名稱Generalizing from Limited Resources in the Open World讀者反饋
書目名稱Generalizing from Limited Resources in the Open World讀者反饋學(xué)科排名
作者: folliculitis 時(shí)間: 2025-3-21 22:12
Stadtstruktur und Stadtbild im Wandel point cloud data is utilized for machine vision tasks. To address this, we propose a point cloud compression framework that simultaneously handles both human and machine vision tasks. Our framework learns a scalable bit-stream, using only subsets for different machine vision tasks to save bit-rate,作者: Archipelago 時(shí)間: 2025-3-22 02:34 作者: AER 時(shí)間: 2025-3-22 06:02
Die Stadt aus psychologischer Perspektive,ting fault detection algorithms leverage deep neural networks (DNNs) to achieve high detection accuracy under various conditions. However, these methods often introduce considerable delays in fault detection, failing to meet the stringent time requirements for fault detection of UHV DC breakers. To 作者: Libido 時(shí)間: 2025-3-22 11:00
Werner Gephart,Hans Peter Schreiner integrating complex deep learning perception algorithms with autonomous navigation system on limited computing resources of UAV poses a significant challenge. In this paper, we propose a solution by leveraging the co-design of software and hardware in a heterogeneous computing system on the UAV, ma作者: Intercept 時(shí)間: 2025-3-22 13:40 作者: Intercept 時(shí)間: 2025-3-22 17:57 作者: 從容 時(shí)間: 2025-3-23 01:10 作者: 比喻好 時(shí)間: 2025-3-23 03:22 作者: thrombosis 時(shí)間: 2025-3-23 07:51
Stadtvisionen und Alltagspraxen im Konflikt,asting is crucial. In highly complex and interconnected atmospheric systems, the evolution of VIL is often potentially linked to other physical factors such as cloud cover, water vapor, and temperature. However, most previous studies have used various time series prediction methods that only relied 作者: 全面 時(shí)間: 2025-3-23 10:56
https://doi.org/10.1007/978-3-322-90476-8ng visual information from the surroundings. Currently, many pre-trained models and pre-training tasks have been proposed to assist agents in navigating unfamiliar environments using visual and linguistic information. However, ensuring that the agent stops near the endpoint is a challenging problem.作者: Permanent 時(shí)間: 2025-3-23 15:09 作者: fluffy 時(shí)間: 2025-3-23 20:04 作者: Exonerate 時(shí)間: 2025-3-24 01:13
Fakult?t für Architektur und Raumplanungnature of real-world scenarios where systems encounter unknown objects. Unlike existing OWOD approaches which often rely on manually selected unknown proposals, we introduce an Adaptive Semantic-Degrade Learning framework. This framework, inspired by cognitive development theory, guides the model to作者: glans-penis 時(shí)間: 2025-3-24 04:40 作者: 山羊 時(shí)間: 2025-3-24 08:05 作者: 任意 時(shí)間: 2025-3-24 14:17 作者: ARBOR 時(shí)間: 2025-3-24 15:05
Toward Efficient Deep Spiking Neuron Networks: A Survey on?Compression and asynchronous computation. When deployed on neuromorphic chips, DSNNs offer significant power advantages over Deep Artificial Neural Networks (DANNs) and eliminate time and energy consuming multiplications due to the binary nature of spikes (0 or 1). Additionally, DSNNs excel in processing tempo作者: vocation 時(shí)間: 2025-3-24 22:21 作者: 水土 時(shí)間: 2025-3-24 23:58 作者: relieve 時(shí)間: 2025-3-25 04:04 作者: CAMP 時(shí)間: 2025-3-25 08:38
CafeLLM: Context-Aware Fine-Grained Semantic Clustering Using Large Language Modelsed and esoteric in many domains, presenting unique challenges that conventional named entity recognition (NER) or clustering methods fail to address. Here, we present CafeLLM, a Context-Aware Fine-grained clustering method that uses Large Language Models (LLMs) to cluster terms or phrases from these作者: 思想 時(shí)間: 2025-3-25 14:56 作者: Vaginismus 時(shí)間: 2025-3-25 18:26
MADP: Multi-modal Sequence Learning for?Alzheimer’s Disease Prediction with?Missing Dataease progression and improving the quality of life for affected individuals. A significant challenge in this context is the substantial amount of missing data, which arises due to the variable health status of subjects or other unpredictable circumstances. Moreover, existing methods struggle to accu作者: JUST 時(shí)間: 2025-3-25 22:06 作者: gusher 時(shí)間: 2025-3-26 02:57
Improved VLN-BERT with?Reinforcing Endpoint Alignment for?Vision-and-Language Navigationng visual information from the surroundings. Currently, many pre-trained models and pre-training tasks have been proposed to assist agents in navigating unfamiliar environments using visual and linguistic information. However, ensuring that the agent stops near the endpoint is a challenging problem.作者: CAB 時(shí)間: 2025-3-26 04:58
Bridging the Language Gap: Domain-Specific Dataset Construction for Medical LLMss a variety of tasks such as text generation, translation, and question answering. However, their effectiveness in specialized domains is constrained by the lack of domain-specific data. This paper presents an effective methodology for constructing domain-specific datasets using domain-specific corp作者: 我就不公正 時(shí)間: 2025-3-26 09:36 作者: ticlopidine 時(shí)間: 2025-3-26 13:30
Semantic-Degrade Learning Framework for?Open World Object Detectionnature of real-world scenarios where systems encounter unknown objects. Unlike existing OWOD approaches which often rely on manually selected unknown proposals, we introduce an Adaptive Semantic-Degrade Learning framework. This framework, inspired by cognitive development theory, guides the model to作者: 結(jié)果 時(shí)間: 2025-3-26 19:44
Multi-modal Prompts with?Feature Decoupling for?Open-Vocabulary Object Detectionor training. The Prompt serves as a template to assist in the construction of textual descriptions for categories. With the development of open-vocabulary object detection, multi-modal prompts with better performance have emerged. However, existing multi-modal prompts fail to align the context and o作者: 小蟲 時(shí)間: 2025-3-26 23:06 作者: 有發(fā)明天才 時(shí)間: 2025-3-27 03:37 作者: Cacophonous 時(shí)間: 2025-3-27 07:55 作者: NAUT 時(shí)間: 2025-3-27 09:28
Robust Autonomous Unmanned Aerial Vehicle System for?Efficient Tracking of?Moving Objectsion algorithms to create an autonomous, robust, and stable AUAV system for tracking moving objects. By achieving autonomy control with the limited resources on the UAV, we extend the usability, offering new possibilities for various domains such as agriculture, search and rescue, and infrastructure inspection.作者: 戲法 時(shí)間: 2025-3-27 17:11
Adapter-Based Contextualized Meta Embeddingsne tuned ensemble on sentence classification tasks. Our results underscore the potential of parameter-efficient fine-tuning of ensembles as efficient and effective alternatives to full fine-tuning and standard ensemble methods.作者: 節(jié)省 時(shí)間: 2025-3-27 20:11
Towards Point Cloud Compression for?Machine Perception: A Simple and?Strong Baseline by?Learning thels with fewer bits, saving bit-rate. Conversely, for more complex tasks (.., segmentation) or objects/scenarios, we use deeper depth levels with more bits to enhance performance. Experimental results on various datasets (.., ModelNet10, ModelNet40, ShapeNet, ScanNet, and KITTI) show that our point c作者: 假裝是我 時(shí)間: 2025-3-28 00:40 作者: 價(jià)值在貶值 時(shí)間: 2025-3-28 04:18
Towards Efficient Fault Detection of?Ultra-High Voltage Direct Current Circuit Breakerslarge amounts of fault case data. Therefore, we propose a self-supervised learning module for the proposed framework to pretrain the detection model using normal case data and finetune it using a small amount of fault case data. Experimental results demonstrate that the detection model trained with 作者: lesion 時(shí)間: 2025-3-28 07:51
Entity Augmentation for?Efficient Classification of?Vertically Partitioned Data with?Limited Overlap Augmentation technique generates meaningful labels for activations sent to the host, regardless of their originating entity, enabling efficient VFL without explicit entity alignment. With limited overlap between training data, this approach performs substantially better (e.g. with 5% overlap, 48.1%作者: collagen 時(shí)間: 2025-3-28 11:15
CafeLLM: Context-Aware Fine-Grained Semantic Clustering Using Large Language Modelsphase, texts are paired in an iterative process to determine if they belong in the same cluster. Overall, we empirically demonstrate that CafeLLM is effective in clustering fine-grained and specialized textual datasets, providing users with a tool to automate and streamline the organization of such 作者: 有抱負(fù)者 時(shí)間: 2025-3-28 15:55 作者: endocardium 時(shí)間: 2025-3-28 21:59 作者: 使害怕 時(shí)間: 2025-3-28 23:46
Improved VLN-BERT with?Reinforcing Endpoint Alignment for?Vision-and-Language Navigationss Rate (SR) on the seen and unseen validation sets of the R2R dataset, respectively. Furthermore, inspired by Airbert, we combine shuffling loss with the reinforcing endpoint alignment task, resulting in a new model named SREA-VLN-BERT. SREA-VLN-BERT achieves improvements of 3.53% and 0.94% in SR o作者: 語源學(xué) 時(shí)間: 2025-3-29 04:20
Bridging the Language Gap: Domain-Specific Dataset Construction for Medical LLMsks. A bidirectional encoder representation from transformer-based comparative analysis revealed comparable performance. The objective is to streamline LLM applications across diverse domains, thereby enhancing language model efficiency. In the future, our efforts will be directed towards implementin作者: Modicum 時(shí)間: 2025-3-29 09:53
Integrating Text-to-Image and?Vision Language Models for?Synergistic Dataset Generation: The Creatio increased by 15% (from 0.54 to 0.625), BLEU score by 20% (from 0.026 to 0.032), and ROUGE-L score by 18% (from 0.20 to 0.235). These results demonstrate substantial enhancements in the multimodal model’s performance. The dataset is specifically designed to support the development and fine-tuning of作者: debase 時(shí)間: 2025-3-29 12:38
Semantic-Degrade Learning Framework for?Open World Object Detectionchmark validate the progressiveness of our framework. The experimental results show that compared with other state-of-the-art methods, our model achieves nearly 50% improvement in unknown mAP and even higher known detection performance, demonstrating excellent detection performance.作者: Esophagus 時(shí)間: 2025-3-29 16:05 作者: 整潔漂亮 時(shí)間: 2025-3-29 23:46 作者: Trypsin 時(shí)間: 2025-3-30 01:02 作者: In-Situ 時(shí)間: 2025-3-30 08:06 作者: Peristalsis 時(shí)間: 2025-3-30 10:10
Stadtstruktur und Stadtbild im Wandells with fewer bits, saving bit-rate. Conversely, for more complex tasks (.., segmentation) or objects/scenarios, we use deeper depth levels with more bits to enhance performance. Experimental results on various datasets (.., ModelNet10, ModelNet40, ShapeNet, ScanNet, and KITTI) show that our point c作者: NAUT 時(shí)間: 2025-3-30 15:12 作者: 是貪求 時(shí)間: 2025-3-30 17:56
Die Stadt aus psychologischer Perspektive,large amounts of fault case data. Therefore, we propose a self-supervised learning module for the proposed framework to pretrain the detection model using normal case data and finetune it using a small amount of fault case data. Experimental results demonstrate that the detection model trained with 作者: 保守黨 時(shí)間: 2025-3-30 20:43
Stadt und Kulturraum Angloamerika Augmentation technique generates meaningful labels for activations sent to the host, regardless of their originating entity, enabling efficient VFL without explicit entity alignment. With limited overlap between training data, this approach performs substantially better (e.g. with 5% overlap, 48.1%作者: finale 時(shí)間: 2025-3-31 02:09 作者: Influx 時(shí)間: 2025-3-31 06:37 作者: Coronary 時(shí)間: 2025-3-31 09:44
