In the area of computer vision, research on object detection algorithms has grown rapidly as it is the fundamental step for automation, specifically for self-driving vehicles. This work presents a comparison of traditional and deep learning approaches for the task of object detection in traffic ...
Moreover, while the proposed scheme enhances restoration effects considerably, integrating human expert knowledge with AI algorithms for enhanced interaction is crucial for capturing the unique expression and personal style of the artist more accurately during the restoration process. Furthermore, future ...
Object Detectionin your videos: Face Recognitionin your photos and videos: Hardware selection While this software has been tested as runnable on a modest laptop with 8GB RAM and an old core-i3 CPU, it's both a memory and CPU hog even if there's just a single deep object detector, since...
Liu T, Zhang Y, Brockett C, Mao Y, Sui Z, Chen W, Dolan B (2019) A token-level Reference-. free Hallucination Detection Benchmark for Free-form Text Generation Liu X, Lai H, Yu H, Xu Y, Zeng A, Du Z, Zhang P, Dong Y, Tang J (2023) WebGLM: towards an efficient web-enh...
Moreover, common terms such as “paintings”, “sculptures”, “algorithms”, “education” and “teaching” are excluded in the classification task. Table 1 Macro-areas grouping together main keywords related to the main technologies for enhancing the fruition of artefacts in traditional museums ...
(NLMS)adaptive filter. They assumed that both facial ROI and background follow theLambertian modeland share the samelight source. The discriminative response map fitting[34]and Kanade–Lucas–Tomasi[35]algorithms were used for face detection and tracking to address rigid head motion. Subsequently, ...
By reviewing both existing and new ideas, this survey gives a complete overview of the concepts, theories, algorithms, and applications related to background modeling and foreground detection. First, an introduction to background modeling and foreground detection for beginners is provided. For this, ...
Deep learning algorithms [18] which driven by data have developed significantly and are widely used in medical domain [1, 8]. As the carrier of TCM knowledge and information, determining how to apply deep learning to formulas for mining becomes a novel topic. The first step of text modeling...
The proposed method employs label propagation algorithms to identify the identities of unlabeled packages, relying on a specially constructed non-negative sparse graph. To optimize their strategy for handling unlabeled data, they experimented with adjusting the proportion of labeled software modules between...
According to this definition of load balancing, scheduling algorithms do the task of load balancing. For this reason, we first surveyed and analyzed the load balancing schedulers in Hadoop. 4.1.1.1 FIFO scheduling FIFO is the default scheduler in Hadoop that operates on a queue of jobs. In ...