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Graph neural networks (GNNs) have gained traction and have been applied to various graph-based data analysis tasks due to their high performance. However, a major concern is their robustness, particularly when faced with graph data that has been ...

• Proposed keypoint-based method for estimating cabbage head diameters with occlusion.
• Introduced an improved deep learning model, YOLOv8n-Cabbage Keypoints (YOLOv8n-CK).
• Cabbage head diameters estimated via various operations.
• ...

Accurate and rapid estimation of cabbage head diameters is critical for precise decision-making in cabbage-harvesting equipment, thereby ensuring the quality of cabbage head harvesting. However, mature cabbage heads are enveloped by layers of ...

Multi-modal Unsupervised Domain Adaptation (MM-UDA) for large-scale 3D semantic segmentation involves adapting 2D and 3D models to a target domain without labels, which significantly reduces the labor-intensive annotations. Existing MM-UDA methods have ...

Few-shot anomaly classification (FSAC) is a vital task in manufacturing industry. Recent methods focus on utilizing CLIP in zero/few normal shot anomaly detection instead of custom models. However, there is a lack of specific text prompts in anomaly ...

• A method for assessing fish feeding intensity from thumbnail images of feeding splashes is proposed.
• Adaptive tuning of receptive fields based on a multi-kernel selection mechanism.
• Development of a semi-supervised object detector ...

Assessment of fish feeding intensity provides effective feedback on fish starvation, which is important for improving feed utilisation and reducing water pollution. The vigorous gathering, jumping, or chasing of fish during feeding produces ...

Few-shot intent classification and slot filling are important but challenging tasks due to the scarcity of finely labeled data. Therefore, current works first train a model on source domains with sufficiently labeled data, and then transfer the model to ...

In this work, a multiple-relaxation-time lattice Boltzmann (MRT-LB) model based on discrete Hermite moments is proposed for nonlinear convection-diffusion equations (NCDEs). First, we use the block-weighted orthogonality of Hermite matrix to give ...

In automatic train operation, non-contact train obstacle detection systems have replaced traditional manual sighting verification. One obstacle detection system usually combines multiple sensors including high-definition cameras, lasers, etc., and these ...

• A strawberry feature adaptive fusion module was proposed.
• An efficient with simple structure decoupled head prediction network was used to generate the strawberry mask.
• Individual strawberry mask was extracted for hue, saturation, ...

Strawberry detection and ripeness classification are important concerns in robotic harvesting, as precondition for efficient and nondestructive picking. However, the different sizes and overlap of strawberries complicate detection, and research ...

Cross-modal Unsupervised Domain Adaptation (UDA) becomes a research hotspot because it reduces the laborious annotation of target domain samples. Existing methods only mutually mimic the outputs of cross-modality in each domain, which enforces the class ...

Object part parsing involves segmenting objects into semantic parts, which has drawn great attention recently. The current methods ignore the specific hierarchical structure of the object, which can be used as strong prior knowledge. To address this, we ...

As the scale of data shows rapid growth in various fields, big data’s vast amount of information can facilitate scientific discovery or decision-making. Deep neural network prevails in modeling big data such as images and text in computer vision ...

• A deep neural network CLDNSR is proposed for high-dimensional tabular data.
• A serial regularization method is proposed to handle high-dimensional features.
• A tabular contrastive learning method is proposed for DNSR pre-training.

Self-Supervised Learning (SSL) is a viable technique to unleash the scalability and generalization of the network. Nevertheless, the representations learned by existing 3D SSL are still insufficient for point cloud shape analysis. Compared to ...

• An automatic detection system for fertilizer deposition distribution was designed.
• Combining Swin Transformer and PANet network were used in the detection.
• A granular fertilizer mask generation network is proposed for small and ...

Beginning with the problems of high cost, low efficiency and high working intensity of traditional granular fertilizer deposition distribution detection methods, this study proposes an automatic detection system of granular fertilizer deposition ...

When only users’ preferences and interests are considered by a recommendation algorithm, it will lead to the severe long-tail problem over items. Therefore, the unfair exposure phenomenon of recommended items caused by this problem has attracted ...

In this work, we present a unified framework of phase-field-based multiple-relaxation-time lattice Boltzmann (MRT-LB) method for incompressible multiphase flows with density and viscosity contrasts where a block-lower-triangular relaxation matrix ...

With the wide application of recommender systems, the potential impacts of recommender systems on customers, item providers and other parties have attracted increasing attention. Fairness, which is the quality of treating people equally, is also becoming ...

Persistent memory (PM) provides byte-addressability, low latency as well as data persistence. Recently, a new feature called eADR is available on the 3rd generation Intel Xeon Scalable Processors with the 2nd generation Intel Optane PM. eADR ...

Cancer prediction based on microarray data can facilitate the molecular exploration of cancers, thus building more accurate cancer prediction models is essential. This study focuses on a deep learning-based cancer prediction model. ...

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• TEDAN is proposed for cancer prediction with HDLSS microarray data.
• The ...

Accurate real-time kinematics model is very important for the control of a skid-steering mobile robot. In this study, the kinematics model of the skid-steering mobile robots was first designed based on instantaneous rotation centers (ICRs). Then, the ...