In this work, we establish that the lack of generalization is mainly due to the channel mismatch, i.e. different recording conditions between the trained and untrained corpus. Additionally, we observe that traditional channel normalization techniques are not effective in improving cross-corpus ...
Background In the medical imaging domain, deep learning‐based methods have yet to see widespread clinical adoption, in part due to limited generalization performance across different imaging devices and acquisition protocols. The deviation between estimated brain age and biological age is an established...
此外,CN和SN的组合在保持较高源精度的同时,具有最好的泛化性能。 3.3. Cross-dataset Generalization in NLP 为了证明CN和SN是独立于应用领域的,还评估了它们在NLP区域的二元情感分类设置上的泛化鲁棒性。模型在IMDb数据集上进行训练,在SST-2数据集上进行测试。按照[16]的设置,使用GloV e[36]单词嵌入和卷积神经...
pretrained-modelscross-modalmultimodalcross-modal-generalization UpdatedSep 30, 2024 Python yisun98/SOLC Star170 Code Issues Pull requests Remote Sensing Sar-Optical Land-use Classfication Pytorch Pytorch高分辨率遥感语义分割/地物分割/地物分类 pytorchremote-sensingsegmentationcross-modalmulti-modalmulti-sourcede...
In this paper, we present a simple, flexible, and general method for semantic segmentation, termed Cross-Dataset Collaborative Learning (CDCL). Given multiple labeled datasets, we aim to improve the generalization and discrimination of feature representations on each dataset. Specifically, we first ...
Fig. 2. Approaches to geographic generalization in model training: 1) ‘Within-site’ training in which training data from site 1 is used to predict site 1; 2) ‘Cross-site’ training in which training data from site 1 is used to predict site 2; 2) ‘Transfer learning’ in which a ...
Data for the four pretrained regional models come from Northern Hemisphere countries, whereas the generalization test was conducted in Chile located in the Southern Hemisphere. It is believed the geographical and meteorological differences are significant25 enough to assess the generalization performance of...
This paper presents a comparative study for the most common Deep Learning (DL) and Machine Learning (ML) algorithms employed for short-term solar irradiance forecasting. The dataset was gathered in Islamabad during a five-year period, from 2015 to 2019, at hourly intervals with accurate ...
The cross-dataset analysis has shown that the generalization power of deep learning models is far from acceptable for the task since accuracy drops from 87.68% to 56.16% on the best evaluation scenario. These results highlighted that the methods that aim at COVID-19 detection in CT-images have...
[COLM 2024] LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition - sail-sg/lorahub