Results 71 to 80 of about 414 (185)
ABSTRACT Handwritten Dongba Character Recognition (HDCR) contains a large number of visually similar characters with subtle and fragile edge cues, posing severe challenges to feature learning. To address this issue, an Edge Channel Aggregation Network (EdgeCANet) model is proposed.
Xiali Li +3 more
wiley +1 more source
Task‐Aligned Haze Removal With Semantic‐Aware Fusion and Contrast Self‐Correction
ABSTRACT Adverse haze conditions introduce complex degradations that obscure scene details and distort structural cues critical for object detection, posing persistent challenges for vision‐based sensing systems. Although existing haze removal methods have achieved notable improvements in visual clarity, their optimisation objectives are often ...
Jinbin Wang +5 more
wiley +1 more source
Transference of bilinear multiplier operators on Lorentz spaces
We prove a DeLeeuw type theorem of transference of boundedness for modulation invariant multiplier operators between the groups defined by the real line and the torus.
Blasco, Oscar, Villarroya, Francisco
openaire +4 more sources
A Lightweight Hybrid Network for Medical Image Segmentation With Adaptive Feature Selection
ABSTRACT Accurate medical image segmentation with low model complexity remains difficult because lesions are often small in scale and boundary cues are easily corrupted by noise. Although recent segmentation methods have achieved strong performance, many of them rely on increasingly complex architectures with high computational costs, limiting their ...
Zhouwei Lin +7 more
wiley +1 more source
TMSA‐Net: Transformer‐Based Multi‐Scale Attention U‐Net for Flood Image Segmentation
ABSTRACT Flood detection is essential for real‐time applications, including disaster management, emergency response, and alerting people in flood zones. For successful flood detection, accurate flood region segmentation is essential. However, the flood region segmentation is challenging due to the complex background and occlusions with debris and the ...
Parham Imanzadeh Charandabi +3 more
wiley +1 more source
Regularized reduced rank regression for mixed predictor and response variables
Abstract In this paper, we introduce the Generalized Mixed Regularized Reduced Rank Regression model (GMR4), an extension of the GMR3 model designed to improve performance in high‐dimensional settings. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables, while also allowing for mixed‐type predictors through optimal ...
Lorenza Cotugno +2 more
wiley +1 more source
Transference and Restriction of Bilinear Fourier Multipliers on Orlicz Spaces
AbstractLet G be a locally compact abelian group with Haar measure $$m_G$$ m G and let $$\Phi _i$$ Φ i , $$i=1,2,3$$ i
Blasco, Oscar, Üster, Rüya
openaire +1 more source
A Real‐Time Multi‐Scale Neural Representation for Complex Surface Reflectance
Abstract Recent machine learning methods have significantly advanced the state of the art in the classic problem of representing surface appearance over angle, space, and scale. The models tend, however, to be relatively heavy compared to traditional fixed‐function representations, making real‐time application challenging.
Heikki Timonen +2 more
wiley +1 more source
On some bilinear Fourier multipliers with oscillating factors, I
For s>0, s≠1, bilinear Fourier multipliers of the form ei(∣∣ξ∣∣s+∣∣η∣∣s+∣∣ξ+η∣∣s)σ(ξ,η) are considered, where σ(ξ,η) belongs to the Hörmander class Sm1,0(R2n). A criterion for m to ensure the L∞×L∞→L∞, L1×L∞→L1, and L∞×L1→L1 boundedness of the corresponding bilinear operators is given.
Kato, Tomoya +3 more
openaire +3 more sources
Real‐time by‐example texture synthesis and filtering using local statistics exchange
Abstract Real‐time by‐example texture synthesis is used in interactive virtual worlds to generate the appearance of an unbounded surface from an exemplar texture with as few repetitions as possible. Currently, leading real‐time methods rely on a tiling and blending scheme which is known to synthesize well texture patterns with little spatial ...
Nicolas Lutz, Guillaume Gilet
wiley +1 more source

