Weakly supervised whole slide image classification is usually formulated as a multiple
instance learning (MIL) problem, where each slide is treated as a bag, and the patches cut …

Artificial intelligence (AI) holds significant promise in transforming medical imaging,
enhancing diagnostics, and refining treatment strategies. However, the reliance on …

Existing pulmonary nodule detection methods often train models in a fully-supervised setting
that requires strong labels (ie, bounding box labels) as label information. However, manual …

Probabilistic-based non-linear dimensionality reduction (PB-NL-DR) methods, such as t-
SNE and UMAP, are effective in unfolding complex high-dimensional manifolds, allowing …

Visual-based perception is the key module for autonomous driving. Among those visual
perception tasks, video object detection is a primary yet challenging one because of feature …

Existing two-stage methods for 3D Human Pose Estimation often use 2D poses as input,
which are then lifted to obtain 3D representations. This typically involves frame-by-frame …

This research requires to improve the accuracy of early diabetic forecasting in a human body
or patient by applying diverse machine learning approaches. Approaching to creation of …