… pseudo labels, degrading the student model significantly. To … reconstruction of stereo
endoscope image. Specifically, two novel modules are introduced: 1) a semi-supervised teacher …

… a large difference between teacher and student networks for anomalous images. In the …
be differentiated between student and teacher networks. The reconstruction network generates …

… teacherstudent DNN strategy for low-dose CT image reconstruction via meta-learning strategy…
Specifically, this strategy mainly consists of two network, ie, teacher network and student …

… imaging tasks such as image reconstruction, super-resolution, and object detection.
Specifically in Magnetic Resonance Imaging (MRI) acceleration, the top five performing methods …

… We observed that the student network trained with the assistance of the teacher using our …
The CPU running time for single image reconstruction for T-DC-CNN and S-DC-CNN are …

… In the MTKDSR framework, we train the student model SMT using these LR patches and
SR images generated from two teacher networks instead of HR images by applying (1)–(6) …

… the teacher model. To further advance the performance and tackle the problem of input inconsistency
between the student and teacher … -rich teacher models to extract image features as …

… where teacher and student networks try to reconstruct HR image … in that our teacher takes
ground-truth HR images as inputs, … powerful feature representations for image reconstruction. …

… variables is increased, image reconstruction is improved, but the … After the teacher model is
trained, we construct a student … For the student, we optimize the reconstruction loss as well as …

… We propose the framework for single image reconstruction … teacher model requires continuous
frames as input and our proposed student+teacher model only needs a single RGB image …