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Found 11 papers, 3 papers with code
HSR-Diff: Hyperspectral Image Super-Resolution via Conditional Diffusion Models
Despite the proven significance of hyperspectral images (HSIs) in performing various computer vision tasks, its potential is adversely affected by the low-resolution (LR) property in the spatial domain, resulting from multiple physical factors.
RZCR: Zero-shot Character Recognition via Radical-based Reasoning
The long-tail effect is a common issue that limits the performance of deep learning models on real-world datasets.
Uncovering the Over-smoothing Challenge in Image Super-Resolution: Entropy-based Quantification and Contrastive Optimization
PSNR-oriented models are a critical class of super-resolution models with applications across various fields.
DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network
Discriminative correlation filters (DCF) and siamese networks have achieved promising performance on visual tracking tasks thanks to their superior computational efficiency and reliable similarity metric learning, respectively.
Hyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning
In contrast to previous approaches, we do not impose restrictions over the source data sets, in which they do not have to be collected by the same sensors as the target data sets.
Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map
Benefiting from its ability to efficiently learn how an object is changing, correlation filters have recently demonstrated excellent performance for rapidly tracking objects.
Multi-Modal Subjective Context Modelling and Recognition
Second, existing models typically assume that context is objective, whereas in most applications context is best viewed from the user's perspective.
Decoder Choice Network for Meta-Learning
This work proposes a method that controls the gradient descent process of the model parameters of a neural network by limiting the model parameters in a low-dimensional latent space.
DS-VIO: Robust and Efficient Stereo Visual Inertial Odometry based on Dual Stage EKF
This paper presents a dual stage EKF (Extended Kalman Filter)-based algorithm for the real-time and robust stereo VIO (visual inertial odometry).
Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network
Recent research has shown that using spectral–spatial information can considerably improve the performance of hyperspectral image (HSI) classification.
Learning Bayesian Network Equivalence Classes with Ant Colony Optimization
Bayesian networks are a useful tool in the representation of uncertain knowledge.
