segmentation

"分割が効く理由は、コンテキストウィンドウの「密度」にあります。"

"In a word, the task is to take a cross-section of colon tissue seen under a microscope, and 'draw the outline', 'classify into 6 types', and 'count the number' of all cell nuclei."

"The essence of COSAS is asking whether it can correctly operate on images from different organs and different scanners than those it learned from, not just simply coloring them."

"I have strong skills and have worked on several projects, along with two research papers on brain MRI segmentation."

"The proposed platform is designed to carry out image processing tasks in real-time and on device, reducing video processing overheads, and thus the overall latency."

"We further observe that XAttnRes alone, even without skip connections, achieves performance on par with the baseline, suggesting that learned aggregation can recover the inter-stage information flow traditionally provided by predetermined connections."

"Meta released SAM 3.1, improving the ability to track multiple objects in videos."

"The new capabilities use AI to discover, understand and explain application behavior and then generate precise, enforcement-ready policies to allow organizations to accelerate segmentation initiatives, strengthen controls with confidence"

"Also, an interesting finding that training for automated labels may amplify bias in your model by 40%."

"Xshield AI Agent is designed to accelerate policy design and rollout from days to minutes by allowing organizations to rapidly isolate critical systems and contain lateral movement during an active breach, […]"

"Experimental results demonstrate that MNAS-Unet outperforms NAS-Unet and other state-of-the-art models in segmentation accuracy on several medical image datasets..."

"The model is incredibly accurate on mazes up to 64x64, but starts to struggle with "global" logic on 127x127 scales, a classic challenge for CNNs without global attention."

"In this blog post, we demonstrate how Hexagon collaborated with Amazon Web Services to scale their AI model production by pretraining state-of-the-art segmentation models, using the model training infrastructure of Amazon SageMaker HyperPod."

"Extensive experiments on five public benchmarks (Kvasir-SEG, CVC-300, CVC-ColonDB, CVC-Clinic, and PolypGen) demonstrate consistent state-of-the-art performance, with 3-8% Dice improvements and 10-20% higher "

"We propose a novel, model-agnostic method for detecting annotation errors by analyzing the Cumulative Sample Loss (CSL)--defined as the average loss a frame incurs when passing through model checkpoints saved across training epochs."

"The proposed method achieves a Dice Similarity Score (DSC) of 0.900 for Whole Tumor (WT) segmentation on the BraTS2021 validation set, demonstrating performance comparable to leading models."

"The key to understanding segmentation is the difference in the handling of Stuff (non-individual areas: sky, road, water, etc.) and Things (individual objects: people, cars, dogs, etc.)."

"In the business world, Object Detection is the most cost-effective and widely applicable."

"The workflow works by generating a base image without any LoRAs. SAM model is used to segment individual characters, allowing different LoRAs to be applied to each segment. Finally, the segmented result is inpainted back into the original image."

"I would like any recommendations on the tools available."

"By evaluating and ranking the datasets, performing comprehensive analyses, generating fused datasets, conducting external validation, and making our implementation p"

"I would like to build a strong foundation and understand the basic concepts."

"FORTRESS achieves state-of-the-art performance on the culvert sewer pipe defect dataset, while significantly reducing the number of trainable parameters, as well as its computational cost."

"This article discusses the implementation of tokenization and word segmentation."

"CamVid is a standard benchmark dataset used for research and evaluation of semantic segmentation (pixel-wise semantic classification of images) in the fields of autonomous driving and robotics."

"UltraLBM-UNet is a novel model for skin lesion segmentation."

"The article focuses on surgical scene segmentation using a spike-driven video transformer."

"CoSeNet is a novel approach for optimal segmentation of correlation matrices."

"Proprioception Enhances Vision Language Model in Generating Captions and Subtask Segmentations for Robot Task"

"The paper focuses on joint optics-sensor-model co-design for semantic segmentation."