Underwater image enhancement (UIE) is crucial for high-level vision in underwater robotics. While convolutional neural networks (CNNs) have made significant achievements in UIE, the locality of convolution poses a challenge in capturing the global context. In contrast, transformer-based networks, adept at handling long-range dependencies, have shown promise in various vision … [Read more...] about WaterFormer: A Global–Local Transformer for Underwater Image Enhancement With Environment Adaptor
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Vision-Based Cow Tracking and Feeding Monitoring for Autonomous Livestock Farming: The YOLOv5s-CA+DeepSORT-Vision Transformer
Animal tracking and feeding monitoring is crucial for automatic individual cow welfare measurement and naturally becomes a prerequisite for autonomous livestock farming systems. The deformable body posture and irregular movement of cows under complex farming environments make tracking of individual animals in a herd very challenging. To tackle the above challenge, a deep … [Read more...] about Vision-Based Cow Tracking and Feeding Monitoring for Autonomous Livestock Farming: The YOLOv5s-CA+DeepSORT-Vision Transformer
USMA-BOF: A Novel Bag-of-Features Algorithm for Classification of Infected Plant Leaf Images in Precision Agriculture
The automatic recognition and classification of infected plant leaves play an important role in precision agriculture and in helping to improve crop yields. With the advancements in the fields of artificial intelligence and computer vision, an exponential progress has been observed in their applications to agriculture, such as in plant leaf disease detection and subsequent … [Read more...] about USMA-BOF: A Novel Bag-of-Features Algorithm for Classification of Infected Plant Leaf Images in Precision Agriculture
Reinforcement-Learning-Based Local Search Approach to Integrated Order Batching: Driving Growth for Logistics and Retail
As an important part of Industry 4.0, a smart warehouse can offer smart tips and operational constraints for users. Improving its work efficiency is a promising growth driver for logistics companies and retailers. Therefore, a reinforcement-learning-based adaptive iterated local search (RAILS) approach is proposed to improve order-picking efficiency for a smart warehouse. A … [Read more...] about Reinforcement-Learning-Based Local Search Approach to Integrated Order Batching: Driving Growth for Logistics and Retail
Toward Lifelong Learning for Industrial Defect Classification: A Proposed Framework
Automatic defect inspection is an important application for the development of smart factories in the era of Industry 4.0. It gathers data from production lines to train a model to automatically recognize certain types of defects. However, the defect types may vary in the production process, and it is difficult for the old model to adapt to new types of defects directly. … [Read more...] about Toward Lifelong Learning for Industrial Defect Classification: A Proposed Framework
