AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
A comparative analysis of existing studies is presented to highlight the evolution of deep learning techniques and their effectiveness in improving recognition accuracy and computational efficiency and emerging research directions are outlined to provide insights for future research.
This survey provides a comprehensive evaluation of various deep learning-based segmentation architectures, covering a wide range of models, from traditional ones like FCN and PSPNet to more modern approaches like SegFormer and FAN, and proposes to evaluate the methods in terms of temporal consistency and corruption vul...
Experimental results demonstrate that the proposed system framework provides consistent identification monitoring performance, stable multi-object tracking capabilities, and an efficient event management mechanism for typical indoor surveillance scenarios.
This study focused on a precise and real-world object detection method for visually challenged persons, developing a novel Equilibrium Optimizer-based Real-Time Object Detection and Classification Framework to support VIP (EORTODCF-VIP).
Object and color detection is an important part of visual recognition and scene understanding, because recognizing an object together with its color provides the contextual cues needed to interpret real-world situations. Accurate detection is difficult, however, because of changes in lighting, complex backgrounds, and...
This work provides a systematic review of TBPS by formalizing the problem setting and presenting a structured taxonomy of representative methods along four key technical dimensions: external knowledge-based approaches that leverage semantic priors to alleviate the inherent modality gap between visual and textual data.
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