Image Classification

Deformable convolution networks have recently become popular for many computer vision tasks, especially for semantic segmentation, because of their exceptional capabilities in dynamic spatial modeling. However, due to th…

Semantic Segmentation Image Classification Edge Detection

One Loop, Two Gains: Can Active Learning win the Lottery for Free?

2026-09-09 · Benedikt Tscheschner, Eduardo Veas, Marc Masana arxiv

The lottery ticket hypothesis posits the existence of winning tickets: sparse subnetworks that, when trained in isolation from their original initialization, match the accuracy of the full dense network. The predominant …

Image Classification Active Learning

Layerwise Tunable Lifting Scheme for the Convolutional Neural Network

2026-09-09 · Abdumannon Yovkochov, An Le, Sungbal Seo, You-Suk Bae 외 arxiv

This work introduces a family of tunable lifting schemes for biorthogonal wavelet filter banks. We propose three lifting strategies: low-pass tuning (LS-LayLatt-LP), high-pass tuning (LS-LayLatt-HP), and a sequential lif…

Image Classification Anomaly Detection

An Attention-Guided Global and Local Fusion Framework for Lesion-Focused Image Classification

2026-09-04 · Mst Shafia Tasnima, Md Samaun Elaheea, Tanjim Taharat Aurpab, Md Musfique Anwar arxiv

Lesion-focused image classification presents a core analytical challenge, as discriminative signals are often sparse, spatially dispersed, and easily obscured by background noise, while conventional convolutional neural …

Image Classification

Quantum-Grassmann-Plucker Token Mixing for Deep Learning-Based Post-Disaster Damage Assessment

2026-08-31 · Kooroush Farahkhah, Umut Lagap, Taha Rezaei, Saman Ghaffarian arxiv

Timely post-disaster building damage assessment from satellite imagery is a critical engineering decision support task, yet it remains constrained by class imbalance, ambiguous intermediate damage states, and limited cro…

Building Damage Assessment Quantum Machine Learning Image Classification

ConCA: Concentration-Aware Channel Attention for Fine-Grained Visual Recognition

2026-08-31 · Yu-Sheng Liu, Yu-Chen Tung arxiv

Lightweight channel attention mechanisms are widely used in image classification, yet their effectiveness in fine-grained visual recognition (FGVR) remains limited. Most modules summarize each channel by global average p…

Fine-Grained Visual Recognition Image Classification

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