Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.

Abstract: Underwater object detection using SONAR images is critical for marine conservation, environmental monitoring, waste management, and rescue operations. In this study, the authors apply ...

New benchmark shows top LLMs achieve only 29% pass rate on OpenTelemetry instrumentation, exposing the gap between ...

These models can now detect and segment images and even create 3D scans of any object or human in them. In videos, these models are capable of segmentation and tracking of objects and humans. Like the ...

We’re introducing SAM 3 and SAM 3D, the newest additions to our Segment Anything Collection, which advance AI understanding of the visual world. SAM 3 enables detection and tracking of objects in ...

This project showcases a sophisticated pipeline for object detection and segmentation using a Vision-Language Model (VLM) and the Segment Anything Model 2 (SAM2). The core idea is to leverage the ...

This project trains machine learning models to predict cancer malignancy and, if malignant, classify the subtype. It provides a Streamlit app with three modes: manual input, CSV upload, and accuracy ...

Astronomers have detected one of the darkest objects ever seen at a record cosmic distance—only with the assistance of gravity. The discovery is an important step toward the observation of dark matter ...

1 Institute of Electronic and Electrical Engineering, Civil Aviation Flight University of China, Guanghan, China 2 School of Information Engineering, Southwest University of Science and Technology, ...

Abstract: Object detection is a fundamental task in computer vision, involving the prediction of bounding boxes and class labels for Regions of Interest (ROI) within images. Traditionally, ...

In object detection models, feature fusion is one of the key techniques for improving model performance (Lian et al., 2024; Deng et al., 2020). The original YOLOv11x employs a relatively simple ...