{"product_id":"computer-vision-eccv-2024-workshops-9783031917202","title":"Computer Vision  ECCV 2024 Workshops","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- Fine-tuning a Multiple Instance Learning Feature Extractor with Masked Context Modelling and Knowledge Distillation.\u003cbr\u003e.- Advancing Medical Radiograph Representation Learning: A Hybrid Pretraining Paradigm with Multilevel Semantic Granularity.\u003cbr\u003e.- Can virtual staining for high-throughput screening generalize?.\u003cbr\u003e.- SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images.\u003cbr\u003e.- A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification.\u003cbr\u003e.- Boosting Medical Image Registration Network Inherently via Collaborative Learning.\u003cbr\u003e.- Genetic Information Analysis of Age-Related Macular Degeneration Fellow Eye Using Multi-Modal Selective ViT.\u003cbr\u003e.- CHOTA: A Higher Order Accuracy Metric for Cell Tracking.\u003cbr\u003e.- Unleashing the Potential of Synthetic Images: A Study on Histopathology Image Classification.\u003cbr\u003e.- Adapting Segment Anything Model to Melanoma Segmentation in Microscopy Slide Images.\u003cbr\u003e.- BATseg: Boundary-aware Multiclass Spinal Cord Tumor Segmentation on 3D MRI Scans.\u003cbr\u003e.- Affinity-VAE: incorporating prior knowledge in representation learning from scientific images.\u003cbr\u003e.- Towards the Discovery of Down Syndrome Brain Biomarkers Using Generative Models.\u003cbr\u003e.- Going Beyond U-Net: Assessing Vision Transformers for Semantic Segmentation in Microscopy Image Analysis.\u003cbr\u003e.- SS-MIL: Attention-Based Selective Correlated Multiple Instance Learning for Whole Slide Image Classification.\u003cbr\u003e.- MicroSSIM: Improved Structured Similarity for Comparing Microscopy Data.\u003cbr\u003e.- Generalized Segmentation for Maxillary Sinus and Mandibular Canal in Dental Panoramic X-rays.\u003cbr\u003e.- MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation.\u003cbr\u003e.- NCT-CRC-HE: Not All Histopathological Datasets Are Equally Useful.\u003cbr\u003e.- Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics.\u003cbr\u003e.- A Novel Approach to Linking Histology Images with DNA Methylation.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53195479384407,"sku":"9783031917202","price":66.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/computer-vision-eccv-2024-workshops-9783031917202","provider":"Book Curl","version":"1.0","type":"link"}