Detection, segmentation, depth and recognition research, plus the vision backbones that keep displacing the last generation.
arXiv:2512. 17605v2 Announce Type: replace-cross Abstract: Robust mammography registration is essential for clinically relevant applications like tracking disease progression in breast tissue.
arXiv:2503. 06473v5 Announce Type: replace-cross Abstract: Growing evidence suggests that layer attention mechanisms, which enhance interaction among layers in deep neural networks, have significantly advanced network architectures.
arXiv:2606. 00987v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have shown strong visual understanding and language-guided grounding abilities, yet their capacity for multi-temporal visual reasoning remains underexplored.
arXiv:2606. 00491v1 Announce Type: cross Abstract: Deep learning-based CT segmentation systems often achieve high accuracy on clean benchmark images, but their performance may degrade under heterogeneous clinical imaging conditions such as noise, resolution loss, contrast variation, intensity shift, and artifacts.
arXiv:2605. 30581v2 Announce Type: replace-cross Abstract: Industrial visual sim-to-real is often described as transferring from synthetic images to real images, but industrial deployment usually involves a broader mismatch between available evidence and required decisions.
arXiv:2604. 09063v3 Announce Type: replace-cross Abstract: Human action recognition is pivotal in computer vision, with applications ranging from surveillance to human-robot interaction.
arXiv:2601. 03309v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models, which integrate pretrained large Vision-Language Models (VLM) into their policy backbone, are gaining significant attention for their promising generalization capabilities.
arXiv:2503. 15639v2 Announce Type: replace-cross Abstract: Modern scene text recognition systems often depend on large end-to-end architectures that require extensive training and are prohibitively expensive for real-time scenarios.
arXiv:2411. 05359v2 Announce Type: replace-cross Abstract: Comprehensive agricultural landscape understanding is critical for addressing global challenges in food security, climate change, and resource management.
arXiv:2606. 02251v1 Announce Type: cross Abstract: Robust state estimation is central to robotic autonomy, yet classical Kalman filters struggle with frequency-dependent disturbances and model mismatch such as sensor vibrations, electromagnetic interference, and periodic noise.
arXiv:2606. 01947v1 Announce Type: cross Abstract: Research and applications in artificial intelligence have recently shifted with the rise of large pretrained models, which deliver state-of-the-art results across numerous tasks.
arXiv:2606. 01689v1 Announce Type: cross Abstract: The detection and segmentation of infrared small targets have important application significance in the fields of surveillance and security, maritime rescue and so on.
arXiv:2606. 01542v1 Announce Type: cross Abstract: Chunked-document retrieval is a common component of retrieval-augmented generation (RAG) systems.
arXiv:2606. 01472v1 Announce Type: cross Abstract: High-stakes production document-generation systems require language models to be adaptive, evidence-grounded, and auditable.
arXiv:2606. 01513v1 Announce Type: cross Abstract: High-stakes enterprise document generation, including financial dispute narratives, compliance notices, and audit summaries, demands schema correctness, policy compliance, and low-latency operation at scale.
arXiv:2606. 01393v1 Announce Type: cross Abstract: Document parsing and recognition are fundamental capabilities for vision-language models (VLMs) and document processing systems.
arXiv:2606. 01293v1 Announce Type: cross Abstract: Accurate segmentation of fetal brain tissues in Magnetic Resonance Imaging (MRI) is critical for early diagnosis of congenital abnormalities and improving prenatal care.
arXiv:2606. 01023v1 Announce Type: cross Abstract: Visual inspection remains the dominant quality-control practice in woven and tufted carpet production, yet it is slow, subjective, and inconsistent at the line speeds and widths of modern looms.
arXiv:2606. 00472v1 Announce Type: cross Abstract: Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feature extraction, and spatial organization analysis.
arXiv:2606. 00380v1 Announce Type: cross Abstract: Machine unlearning removes the influence of specific training data from a trained model without retraining it from scratch.