Overview: Compares the leading computer vision APIs, multimodal AI models, and open-source vision frameworks available in ...
Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional ...
Most people assume object tracking for autonomous flight is very complex, but it doesn’t have to be that way. All you need is ...
ENVIRONMENT: An Investment company is searching for a talented and driven Data Scientist to join their innovative and growing team based in Durbanville, Cape Town. This is an exciting opportunity to ...
Digital addiction (DA) has emerged as a significant global concern, yet traditional diagnostic methods relying on self-report questionnaires face subjective bias and threshold inconsistencies. Recent ...
Background & Motivation Background: Open-Vocabulary Object Detection (OVOD) requires detectors to recognize categories not annotated during training. The mainstream approach leverages the cross-modal ...
Abstract: Recently, new paradigms of camouflaged object detection (COD), such as referring COD (Ref-COD) and collaborative COD (Co-COD), have been proposed to enhance task performance. However, there ...
Rex-Omni is a 3B-parameter Multimodal Large Language Model (MLLM) that redefines object detection and a wide range of other visual perception tasks as a simple next-token prediction problem.
Based on clinical data from the first 24 hours of ICU admission, we used a two-stage feature selection process combining light gradient boosting machine (LightGBM) and Shapley additive explanation ...
Abstract: Abstract: In recent times, deep learning has emerged as one of the powerful tools in the process of object detection. The deep learning algorithms that are used in object detection are ...
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