Accurate and fast object recognition is crucial in applications such as automatic driving and unmanned aerial vehicles. Traditional object recognition methods relying on image-wise computations cannot afford such real-time applications. Object propos...
The effectiveness of depth information in saliency detection has been fully proved. However, it is still worth exploring how to utilize the depth information more efficiently. Erroneous depth information may cause detection failure, while non-salient...
The efficacy of Underwater Camouflaged Object Detection (UCOD) is fundamentally constrained by severe boundary ambiguity, where biological mimicry blends targets into complex backgrounds and aquatic optical degradation erodes edge details. We propose...
Emotion matching prediction between music and video segments is essential for intelligent mobile sensing systems, where multimodal affective cues collected from smart devices must be jointly analyzed for context-aware media understanding. However, tr...
Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the...
Unmanned aerial vehicles (UAVs) equipped with remote-sensing object-detection devices are increasingly employed across diverse domains. However, the detection of small, densely-packed objects against complex backgrounds and at various scales presents...
Object detection in adverse weather remains challenging due to the simultaneous degradation of visibility, structural boundaries, and semantic consistency. Existing restoration-driven or multi-branch detection approaches often fail to recover task-re...
Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to...
At 300 km/h, an end-to-end vision delay of 100 ms corresponds to 8.3 m of unobserved travel; therefore, real-time anomaly monitoring must balance sensitivity with strict tail-latency constraints at the edge. We propose a hybrid cache–retrieval...
Urban building change detection (UBCD) is essential for urban planning, land-use monitoring, and smart city analytics, yet bi-temporal optical methods remain limited by spectral confusion, occlusions, and weak sensitivity to structural change. To ove...
Background: Spatial heterogeneity in tumor tissue has been linked to patient prognosis. To exploit both structural and semantic cues in whole slide images (WSIs), we propose Dual eXplanatory Framework (DuXplore), a dual-branch deep learning framework...