AskScience AMA Series: I am a computer scientist at the University of Maryland, where I research deepfake and audio spoofing defense, voice privacy and security...
reddit.com·19h·
Discuss: r/askscience
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Understanding Cross Task Generalization in Handwriting-Based Alzheimer's Screening via Vision Language Adaptation
arxiv.org·11h
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Apple's LLM Breakthrough
xray.greyb.com·3h·
Discuss: Hacker News
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Anatomy-Aware Lymphoma Lesion Detection in Whole-Body PET/CT
arxiv.org·11h
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Understanding the nuances of human-like intelligence
news.mit.edu·11h
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The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or an LLM (Explained with One Example)
towardsdatascience.com·59m
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CAMP-HiVe: Cyclic Pair Merging based Efficient DNN Pruning with Hessian-Vector Approximation for Resource-Constrained Systems
arxiv.org·11h
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NeuroBridge: Bio-Inspired Self-Supervised EEG-to-Image Decoding via Cognitive Priors and Bidirectional Semantic Alignment
arxiv.org·11h
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Exploiting neuro-inspired dynamic sparsity for energy-efficient intelligent perception
nature.com·16h
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Sim4Seg: Boosting Multimodal Multi-disease Medical Diagnosis Segmentation with Region-Aware Vision-Language Similarity Masks
arxiv.org·11h
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CAMP-VQA: Caption-Embedded Multimodal Perception for No-Reference Quality Assessment of Compressed Video
arxiv.org·11h
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The Robot That Learned to See
dev.to·4h·
Discuss: DEV
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How Machines See: The Power of Computer Vision in AI (Explained for Developers)
dev.to·21h·
Discuss: DEV
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Improving Region Representation Learning from Urban Imagery with Noisy Long-Caption Supervision
arxiv.org·11h
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Leveraging Text-Driven Semantic Variation for Robust OOD Segmentation
arxiv.org·11h
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Automatic segmentation of colorectal liver metastases for ultrasound-based navigated resection
arxiv.org·1d
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Google will peel back a new era of AI images with Nano Banana 2
techradar.com·16h
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A benchmark multimodal oro-dental dataset for large vision-language models
arxiv.org·1d
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Aligning Attention with Human Rationales for Self-Explaining Hate Speech Detection
arxiv.org·11h
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ConeGS: Error-Guided Densification Using Pixel Cones for Improved Reconstruction with Fewer Primitives
arxiv.org·11h
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