Results 21 to 30 of about 4,502,013 (256)

Image augmentation techniques for convolutional neural network [PDF]

, 2022
openUna delle più grandi sfide per le Reti Neurali Convoluzionali, soprattutto ora che vengono utilizzate ampiamente in svariati contesti, è la mancanza di training set adeguati per sessioni di training robuste e meno prone ad overfitting.
BRAVIN, RICCARDO
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Remote Sensing Target Tracking in UAV Aerial Video Based on Saliency Enhanced MDnet

IEEE Access, 2019
Remote sensing target tracking in the aerial video from unmanned aerial vehicles (UAV) plays a key role in public security. As the UAV aerial video has rapid changes in scale and perspective, few pixels in the target region, and multiple similar ...
Fukun Bi, Mingyang Lei, Yanping Wang, Dan Huang   +3 more
doaj   +1 more source

Data augmentation approaches for polyp segmentation [PDF]

, 2022
openImage augmentation, and in general data augmentation techniques, can greatly improve the performances of deep neural networks through the creation of artificial patterns, in fact the presence of these new patterns helps the network to generalise thus
DORIZZA, ALBERTO
core  

data augmentation for chromosomes classification [PDF]

, 2023
openUtilizzo di diversi tipi di data augmentation per ottenere migliori prestazioni durante la classificazione di cromosomi con rete ...
GUGLIELMO, NICOLAS
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Dynamic Adaptive Iterative Generative Adversarial Network for Hyperspectral Image Classification With Class Imbalance

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Small-sample learning improves the problem of limited labeled samples in hyperspectral image (HSI) classification to a greater extent, but still suffers from the severe problem of class imbalance, where minority classes are poorly learned and classified,
Ke Li, Ying Cui, Liguo Wang, Shan Gao, Chunhui Zhao, Tianfang Luo   +5 more
doaj   +1 more source

Cotton Fusarium wilt diagnosis based on generative adversarial networks in small samples

Frontiers in Plant Science, 2023
This study aimed to explore the feasibility of applying Generative Adversarial Networks (GANs) for the diagnosis of Verticillium wilt disease in cotton and compared it with traditional data augmentation methods and transfer learning. By designing a model
Zhenghang Zhang, Zhenghang Zhang, Lulu Ma, Lulu Ma, Chunyue Wei, Mi Yang, Mi Yang, Shizhe Qin, Shizhe Qin, Xin Lv, Xin Lv, Ze Zhang, Ze Zhang   +12 more
doaj   +1 more source

Diffeomorphic transforms for data augmentation [PDF]

, 2022
openL’incremento dei dati è una tecnica ampiamente utilizzata in molti compiti di apprendimento automatico, come la classificazione delle immagini, per ampliare virtualmente la dimensione di dati ed evitare l’overfitting.
COCCO, ALESSIO
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Mean-Weighted Collaborative Representation-Based Spatial-Spectral Joint Classification for Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Collaborative representation (CR) models have been widely used in hyperspectral image (HSI) classification tasks. However, most CR classification models lack stability and generalization when targeting small samples as well as spatial homogeneity and ...
Hongjun Su, Dezhong Shi, Zhaohui Xue, Qian Du   +3 more
doaj   +1 more source

Data Augmentation for Sample Efficient and Robust Document Ranking [PDF]

, 2023
Contextual ranking models have delivered impressive performance improvements over classical models in the document ranking task. However, these highly over-parameterized models tend to be data-hungry and require large amounts of data even for fine-tuning.
Anand, Abhijit, Singh, Jaspreet, Anand, Avishek, Rudra, Koustav, Leonhardt, Jurek   +4 more
core   +1 more source

An Automatic Sample Augmentation Method for Paddy Rice Mapping Based on Segment Anything Model and Phenological Features—A Case Study in Southwest China

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
The remote sensing mapping of paddy rice in Southwest China faces challenges such as fragmented parcels and difficulties in field sample collection, hindering deep learning technology applications. To address sample scarcity for deep learning-based paddy
Ziyi Tang, Xinyi Luo, Zijia Yan, Shiyi Li, Sujie Xiao, Hao Li   +5 more
doaj   +1 more source