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D4SC: Deep Supervised Semantic Segmentation for Seabed Characterization and Uncertainty Estimation for Large Scale Mapping

Development and Validation of a Fully Automated Tool to Quantify 3D Foot and Ankle Alignment using Weight-Bearing CT

Gradient calibration loss for fast and accurate oriented bounding box regression

Oriented object detection has a very wide range of application scenarios. In recent years, a lot of rotation detectors have been designed to achieve high-performance oriented object detection. Intersection-over-union (IoU) is the commonly used …

Not All Boxes Are Equal: Learning to Optimize Bounding Boxes with Discriminative Distributions in Optical Remote Sensing Images

PCGen: A Fully Parallelizable Point Cloud Generative Model

Generative models have the potential to revolutionize 3D extended reality. A primary obstacle is that augmented and virtual reality need real-time computing. Current state-of-the-art point cloud random generation methods are not fast enough for these …

Sample size effect on musculoskeletal segmentation : how low can we go?

Convolutional Neural Networks have emerged as a predominant tool in musculoskeletal medical image segmentation. It enables precise delineation of bone and cartilage in medical images. Recent developments in image processing and network architecture …

Understanding skin color bias in deep learning-based skin lesion segmentation

An end-to-end framework for joint denoising and classification of hyperspectral images

Image denoising and classification are typically conducted separately and sequentially according to their respective objectives. In such a setup, where the two tasks are decoupled, the denoising operation does not optimally serve the classification …

From model-based optimization algorithms to deep learning models for clustering hyperspectral images

Hyperspectral images (HSIs), captured by different Earth observation airborne and space-borne systems, provide rich spectral information in hundreds of bands, enabling far better discrimination between ground materials that are often …

GPU Rasterization-Based 3D LiDAR Simulation for Deep Learning