Generalizing from Limited Resources in the Open World: Second International Workshop, GLOW 2024, Held in Conjunction with IJCAI 2024, Jeju, South Korea, August 3, 2024, Proceedings: Communications in Computer and Information Science, cartea 2160
Editat de Jinyang Guo, Yuqing Ma, Yifu Ding, Ruihao Gong, Xingyu Zheng, Changyi He, Yantao Lu, Xianglong Liuen Limba Engleză Paperback – 10 sep 2024
The 11 full papers and 4 short papers included in this book were carefully reviewed and selected from 22 submissions. They were organized in topical sections as follows: efficient methods for low-resource hardware; efficient fintuning with limited data; advancements in multimodal systems; recognition and reasoning in the open world.
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Specificații
ISBN-13: 9789819761241
ISBN-10: 9819761247
Pagini: 220
Ilustrații: VI, 202 p.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.34 kg
Ediția:2024
Editura: Springer Nature Singapore
Colecția Springer
Seria Communications in Computer and Information Science
Locul publicării:Singapore, Singapore
ISBN-10: 9819761247
Pagini: 220
Ilustrații: VI, 202 p.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.34 kg
Ediția:2024
Editura: Springer Nature Singapore
Colecția Springer
Seria Communications in Computer and Information Science
Locul publicării:Singapore, Singapore
Cuprins
Efficient Methods for Low-resource Hardware.- Towards Point Cloud Compression for Machine Perception: A Simple and Strong Baseline by Learning the Octree Depth Level Predictor.- Toward Efficient Deep Spiking Neuron Networks: A Survey On Compression.- Towards Efficient Fault Detection of UHV DC Circuit Breakers.- Robust Autonomous Unmanned Aerial Vehicle System for Efficient Tracking of Moving Objects.- Efficient Fintuning with Limited Data.- Entity Augmentation for Efficient Classification of Vertically Partitioned Data with Limited Overlap.-CafeLLM: Context-Aware Fine-Grained Semantic Clustering using Large Language Models.- Adapter-Based Contextualized Meta Embeddings.- Advancements in Multimodal Systems.- MADP: Multi-modal Sequence Learning for Alzheimer’s Disease Prediction with Missing Data.- Multi-modal Spatiotemporal Forecasting via Cross-scale Operator Learning and Spatial Representation Aggregation.- Improved VLN-BERT with Reinforcing Endpoint Alignment for Vision-and-Language Navigation.- Bridging the Language Gap: Domain-Specific Dataset Construction for Medical LLMs.- Integrating Text-to-Image and Vision Language Models for Synergistic Dataset Generation: The Creation of Synergy-General-Multimodal Pairs.- Recognition and Reasoning in the Open World.- Semantic-Degrade Learning Framework for Open World Object Detection.- Multi-modal Prompts with Feature Decoupling for Open-Vocabulary Object Detection.- YOLO-FCNET: Enhancing SAR Ship Detection with Fourier Convolution in YOLOv8.