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pro vyhledávání: '"Zhang, Chuanyi"'
Knowledge distillation (KD) is an effective method for compressing models in object detection tasks. Due to limited computational capability, UAV-based object detection (UAV-OD) widely adopt the KD technique to obtain lightweight detectors. Existing
Externí odkaz:
http://arxiv.org/abs/2408.11407
Few-shot classification (FSC) is a fundamental yet challenging task in computer vision that involves recognizing novel classes from limited data. While previous methods have focused on enhancing visual features or incorporating additional modalities,
Externí odkaz:
http://arxiv.org/abs/2408.11297
The development of multi-modal object detection for Unmanned Aerial Vehicles (UAVs) typically relies on a large amount of pixel-aligned multi-modal image data. However, existing datasets face challenges such as limited modalities, high construction c
Externí odkaz:
http://arxiv.org/abs/2406.06230
Detecting objects from Unmanned Aerial Vehicles (UAV) is often hindered by a large number of small objects, resulting in low detection accuracy. To address this issue, mainstream approaches typically utilize multi-stage inferences. Despite their rema
Externí odkaz:
http://arxiv.org/abs/2405.15465
Machine unlearning empowers individuals with the `right to be forgotten' by removing their private or sensitive information encoded in machine learning models. However, it remains uncertain whether MU can be effectively applied to Multimodal Large La
Externí odkaz:
http://arxiv.org/abs/2405.12523
Manually annotating datasets for training deep models is very labor-intensive and time-consuming. To overcome such inferiority, directly leveraging web images to conduct training data becomes a natural choice. Nevertheless, the presence of label nois
Externí odkaz:
http://arxiv.org/abs/2403.15694
Autor:
Li, Jiaqi, Du, Miaozeng, Zhang, Chuanyi, Chen, Yongrui, Hu, Nan, Qi, Guilin, Jiang, Haiyun, Cheng, Siyuan, Tian, Bozhong
Multimodal knowledge editing represents a critical advancement in enhancing the capabilities of Multimodal Large Language Models (MLLMs). Despite its potential, current benchmarks predominantly focus on coarse-grained knowledge, leaving the intricaci
Externí odkaz:
http://arxiv.org/abs/2402.14835
Multimodal movie genre classification has always been regarded as a demanding multi-label classification task due to the diversity of multimodal data such as posters, plot summaries, trailers and metadata. Although existing works have made great prog
Externí odkaz:
http://arxiv.org/abs/2310.08032
Autor:
Pan, Chao, Zhang, Chuanyi
As a general type of machine learning approach, artificial neural networks have established state-of-art benchmarks in many pattern recognition and data analysis tasks. Among various kinds of neural networks architectures, polynomial neural networks
Externí odkaz:
http://arxiv.org/abs/2207.08896
Publikováno v:
In Journal of Environmental Chemical Engineering June 2024 12(3)