Given the significant differences between domains, current unpaired learning methods struggle to accurately map the relationship between rainy and clear images. To this end, we introduce a neural Schrödinger bridge (NSB) for unpaired real-world ...

Due to the miniature scale and limited identifiable features, small objects pose a significant challenge in detection. Improving the accuracy of small object detection is a momentous issue of concern among researchers. Feature pyramid network ...

• Feature Aggregation Network (FAN), a simple and effective method, is proposed.
• Feature-Aware Module narrows the semantic gap that favors detecting small objects.
• A dual top-down pathway enhances spatial and semantic information.

The existing detection models for stored grain pests have low accuracy and poor generalization ability in fine-grained detection tasks involving numerous species, minor inter-class differences, and significant intra-class variations. This study ...

This paper proposes an adaptive graph-based approach for multi-label image classification. Graph-based methods have been largely exploited in the field of multi-label classification, given their ability to model label correlations. Specifically, ...

• A novel graph-based approach for multi-label image classification is proposed.
• It learns adaptively a graph describing label dependencies.
• It is extended to cross-domain settings with an adversarial domain adaptation schema.
• ...

Artificial intelligence models encounter significant challenges due to their black-box nature, particularly in safety-critical domains such as healthcare, finance, and autonomous vehicles. Explainable Artificial Intelligence (XAI) addresses these ...

To gather a significant quantity of annotated training data for high-performance image classification models, numerous companies opt to enlist third-party providers to label their unlabeled data. This practice is widely regarded as secure, even in ...

Satellite-to-ground image synthesis aims at generating a realistic street-view image from its corresponding satellite-view image. Despite the considerable efforts towards improving the geometry structure of the synthetic street-view images, the ...

We propose a concise and consistent network focusing on multi-task learning of Referring Expression Comprehension (REC) and Segmentation (RES) within Visual grounding (VG). To simplify the model architecture and achieve parameter sharing, we ...

• We propose a simple and unified framework for Referring Expression Comprehension and Segmentation, casting visual grounding as a sequence of point generation problem under a common L 1 loss.
• Our Multi-Modal Interaction Fusion enhances ...

Person re-identification has gained significant attention in recent years due to its numerous practical applications in video surveillance. However, while artificial intelligence and deep learning methods have enabled substantial progress in ...

In the citrus orchard environment, accurate counting of the fruit, and the use of lightweight detection methods are the key presteps to automate citrus picking and yield estimations. Most high-precision fruit detection models based on deep ...$$$$$$$$$$

Instance segmentation of faces and mouth-opening degrees is an important technology for meal-assisting robotics in food delivery safety. However, due to the diversity in in shape, color, and posture of faces and the mouth with small area contour, ...

The paper introduces an integrated methodology for license plate character recognition, combining YOLOv8 for segmentation and a CSPBottleneck-based CNN classifier for character recognition. The proposed approach incorporates pre-processing ...

The labeling effort of deep learning-connected projects can introduce unexpected expenditure, especially when we are dealing with a challenging problem representation such as noisy camera images. Instead of a classical semi-supervised concept, ...

An ever-increasing installation of surveillance cameras at different places for ensuring public safety, security and asset protection has triggered the need for intelligent video surveillance to monitor the people and their behavior. Violence ...

Reconstructing the three-dimensional structure of a scene is a classic and fundamental problem in computer vision, but it has been revolutionized by recent advancements in deep machine learning. In this paper, we survey this rich and growing ...

Falls pose a significant risk to elderly people, patients with diseases such as neurological disorders, cardiovascular diseases, and disabled children. This highlights the need for real-time intelligent fall detection (FD) systems for quick ...

• Developed DiverseFALL10500: a comprehensive dataset with 10,500 annotated images.
• Optimized YOLOv8s with focus module and CBAM integration for improved performance.
• Demonstrated superiority over SOTA techniques through extensive ...

Construction and demolition waste (C&DW) materials are highly valuable as, in most cases, they can be reused. In other cases, such material can be highly pollutant. Therefore, their traceability becomes very important in the frame of sustainable ...

Object detection models have been experiencing significant improvements over the years due to advancements in deep learning techniques, increased availability of large-scale annotated datasets, and computational resources. Different object ...

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• Qualitative and Quantitative Comparison of object detection models.
• Assessment of model performance under real-world challenges in environmental scenes.
• Insights into model suitability for environmental monitoring, using detection ...

The digitization of variety identification is of great importance for the improvement of farming practices in date fruit production. In this study, we have developed a hybrid approach called DenseViT-XGB for date fruit variety identification. ...

Recently, the rapid progress of artificial intelligence has enhanced the human-robot relationship through the development of several autonomous robots; such as drones. The overwhelming rise of drones has brought both relevant advantages and ...