Latest AI and machine learning research in schizophrenia for healthcare professionals.
Scanning Probe Microscopy or SPM offers nanoscale resolution but is frequently marred by structured artefacts such as line scan dropout, gain induced noise, tip convolution, and phase hops. While most available methods treat SPM artefact removal as isolated denoising or interpolation tasks, the generative inpainting perspective remains largely unexplored. In this work, we introduce a diffusion bas...
Hallucination detection in captions (HalDec) assesses a vision-language model's ability to correctly align image content with text by identifying errors in captions that misrepresent the image. Beyond evaluation, effective hallucination detection is also essential for curating high-quality image-caption pairs used to train VLMs. However, the generalizability of VLMs as hallucination detectors acro...
Twelve-lead electrocardiography (ECG) is essential for cardiovascular diagnosis, but its long-term acquisition in daily life is constrained by complex...
Vision-Language Models (VLMs) frequently "hallucinate" - generate plausible yet factually incorrect statements - posing a critical barrier to their tr...
Current training-free methods tackle MLLM hallucination with separate strategies: either enhancing visual signals or suppressing text inertia. However...
While large vision-language models (LVLMs) achieve strong performance on multimodal tasks, they frequently generate hallucinations -- unfaithful outpu...
Maintaining background consistency while enhancing foreground quality remains a core challenge in video editing. Injecting full-image information ofte...
Quantitative systems pharmacology (QSP) models require calibration data from published literature, yet manual curation produces inconsistent documenta...
With the rapid advancement of AIGC technology, developing identification methods to address the security challenges posed by deepfakes has become urge...
Accurate tumor analysis is central to clinical radiology and precision oncology, where early detection, reliable lesion characterization, and patholog...
Generative real-world image super-resolution (Real-ISR) can synthesize visually convincing details from severely degraded low-resolution (LR) inputs, ...
Digital subtraction angiography (DSA) is a key imaging technique for the auxiliary diagnosis and treatment of cerebrovascular diseases. Recent advance...
Hallucination has been a significant impediment to the development and application of current Large Vision-Language Models (LVLMs). To mitigate halluc...
Deep learning (DL) methods are currently being explored to restore images from sparse-view-, limited-data-, and undersampled-based acquisitions in med...
Animals integrate information over time and maintain persistent internal representations of cues to guide decision-making. How the underlying behavior...
Background: The rapid growth of public single-cell and spatial transcriptomics repositories has shifted the main bottleneck for atlas-scale integratio...
Large 3D reconstruction models have revolutionized the 3D content generation field, enabling broad applications in virtual reality and gaming. Just li...
Large visual language models (VLMs) have shown strong multi-modal medical reasoning ability, but most operate as end-to-end black boxes, diverging fro...
We present FireRed-OCR, a systematic framework to specialize general VLMs into high-performance OCR models. Large Vision-Language Models (VLMs) have d...
A system that enables blind or visually impaired users to access comics/manga would introduce a new medium of storytelling to this community. However,...