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Jul 2, 2024 · This research aims to develop an optimal CNN model for the classification of blood cells that achieves high accuracy and is also interpretable using explainable ...
1 day ago · In this paper, we provide a new perspective to summarize the theories and methods for training deep SNNs with high performance in a systematic and comprehensive ...
Jul 16, 2024 · DTXNET is a deep neural network which represents the motion equation of the flexible body and task using not only its joint angle, velocity, and torque but also ...
Jul 22, 2024 · These AI-based models can be used in decision-making processes when predicting part quality, tool and machine conditions are essential elements of a system ...
Jul 16, 2024 · This model builds upon the framework of the Detection Transformer (DETR) (45) which was the first deep learning model to perform end-to-end object detection ...
Jul 10, 2024 · In this paper, we provide a new perspective to summarize the theories and methods for training deep SNNs with high performance in a systematic and comprehensive ...
Jul 9, 2024 · In this paper, we present a deep CNN-based approach for multi-class classi ication of three-dimensional (3-D) objects using phase-only digital.
Jul 15, 2024 · Abstract. Two-dimensional phase unwrapping is a fundamental yet vital task in optical imaging and measurement. In this paper, what we believe to be a novel ...
6 days ago · We present a comprehensive neural network to model the deformation of human soft tissues including muscle, tendon, fat and skin. Our approach provides kinematic ...
1 day ago · To accomplish deformable registration, for instance, [50] employed a 5-layer convolutional neural network (CNN) to develop a measure to assess the similarity of ...
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