Deep Learning for Perception and Recognition

The rapid advancement of deep learning technology has brought about transformative breakthroughs in perception and recognition systems across a wide range of applications. In addition to driving innovation in industrial sectors, it has opened up significant opportunities in fields such as intelligen...

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Bibliographische Detailangaben
Format:	Online
Sprache:	Englisch
Veröffentlicht:	MDPI - Multidisciplinary Digital Publishing Institute 2026
Schlagworte:	Photovoltaic panel defects Defect segmentation Deformable attention Feature aggregation Posture recognition Localization FPGA Service robot Sensor fusion Steer-by-wire (SbW) systems Steering-angle prediction Autonomous vehicles (AVs) Convolutional neural network (CNN) Barrier Lyapunov function Coal–gangue detection Object distribution density measurement (ODDM) Relative resolution object scale measurement (RROSM) Label rewriting problem Compact neural network Anti-spoofing detection Swin Transformer ResNet Auto-encoder Hypergraph neural networks Hierarchical representations Node classification Emotion recognition Brain-computer interface Student learning effectiveness State estimation CT image Milling force prediction Coal quality analysis Near-infrared spectroscopy (NIRS) X-ray fluorescence (XRF) Particle size effect Image segment Data-efficient image transformer (DeiT) Landmark localization Biplanar X-ray imaging Projective geometry Hierarchical graph fusion Mid-late multilevel gender-aware strategy Multi-task learning Adversarial attack PSF Rolling shutter CMOS Blast furnace monitoring Time-series anomaly detection Adversarial autoencoder Variational mode decomposition Unsupervised learning Defect detection DINOv2 Stochastic Configuration Network Wind blades YOLOv5 network Underwater image enhancement Underwater non-uniform blur Multi-scale perception Hybrid interaction attention Non-contact sensing Sensor comparison Laser Doppler vibrometer (LDV) Electro-acoustic transducer Musical acoustics String vibration Electric guitar Waveform analysis Skeleton-based action recognition Multimodal learning Contrastive learning Frequency learning Complex-scene image enhancement Multi-type degradation dataset Feature Filter Transformer Gaussian-filter self-attention thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
Online-Zugang:	ONIX_20260416T142754_9783725862665_26
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Deep Learning for Perception and Recognition

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